Bump version: 0.21.1-beta.0 → 0.21.1

We attempted to make pylance optional in
https://github.com/lancedb/lancedb/pull/2156 but it appears this did not
quite work. Users are unable to use lancedb from a fresh install. This
reverts the optional-ness so we can get back in a working state while we
fix the issue.

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.16.1-beta.3"
+current_version = "0.18.0"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

.github/workflows/python.yml

@@ -33,13 +33,14 @@ jobs:
           python-version: "3.12"
       - name: Install ruff
         run: |
-          pip install ruff==0.8.4
+          pip install ruff==0.9.9
       - name: Format check
         run: ruff format --check .
       - name: Lint
         run: ruff check .
-  doctest:
-    name: "Doctest"
+
+  type-check:
+    name: "Type Check"
     timeout-minutes: 30
     runs-on: "ubuntu-22.04"
     defaults:
@@ -54,7 +55,36 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
+      - name: Install protobuf compiler
+        run: |
+          sudo apt update
+          sudo apt install -y protobuf-compiler
+          pip install toml
+      - name: Install dependencies
+        run: |
+          python ../ci/parse_requirements.py pyproject.toml --extras dev,tests,embeddings > requirements.txt
+          pip install -r requirements.txt
+      - name: Run pyright
+        run: pyright
+
+  doctest:
+    name: "Doctest"
+    timeout-minutes: 30
+    runs-on: "ubuntu-24.04"
+    defaults:
+      run:
+        shell: bash
+        working-directory: python
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
           cache: "pip"
       - name: Install protobuf
         run: |
@@ -75,8 +105,8 @@ jobs:
     timeout-minutes: 30
     strategy:
       matrix:
-        python-minor-version: ["9", "11"]
-    runs-on: "ubuntu-22.04"
+        python-minor-version: ["9", "12"]
+    runs-on: "ubuntu-24.04"
     defaults:
       run:
         shell: bash
@@ -127,7 +157,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: python
@@ -157,7 +187,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: python
@@ -168,7 +198,7 @@ jobs:
         run: rm -rf target/wheels
   pydantic1x:
     timeout-minutes: 30
-    runs-on: "ubuntu-22.04"
+    runs-on: "ubuntu-24.04"
     defaults:
       run:
         shell: bash

.github/workflows/rust.yml

@@ -184,15 +184,17 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v4
-      - name: Install dependencies
+      - name: Install dependencies (part 1)
         run: |
           set -e
           apk add protobuf-dev curl clang lld llvm19 grep npm bash msitools sed
-
-          curl --proto '=https' --tlsv1.3 -sSf https://raw.githubusercontent.com/rust-lang/rustup/refs/heads/master/rustup-init.sh | sh -s -- -y
-          source $HOME/.cargo/env
-          rustup target add aarch64-pc-windows-msvc
-
+      - name: Install rust
+        uses: actions-rust-lang/setup-rust-toolchain@v1
+        with:
+          target: aarch64-pc-windows-msvc
+      - name: Install dependencies (part 2)
+        run: |
+          set -e
           mkdir -p sysroot
           cd sysroot
           sh ../ci/sysroot-aarch64-pc-windows-msvc.sh
@@ -264,7 +266,7 @@ jobs:
       - name: Install Rust
         run: |
           Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
-          .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
+          .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc --default-toolchain 1.83.0
         shell: powershell
       - name: Add Rust to PATH
         run: |

.pre-commit-config.yaml

@@ -1,16 +1,22 @@
 repos:
--   repo: https://github.com/pre-commit/pre-commit-hooks
+  - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v3.2.0
     hooks:
       - id: check-yaml
       - id: end-of-file-fixer
       - id: trailing-whitespace
--   repo: https://github.com/astral-sh/ruff-pre-commit
+  - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.8.4
+    rev: v0.9.9
     hooks:
       - id: ruff
-- repo: local
+  # - repo: https://github.com/RobertCraigie/pyright-python
+  #   rev: v1.1.395
+  #   hooks:
+  #     - id: pyright
+  #       args: ["--project", "python"]
+  #       additional_dependencies: [pyarrow-stubs]
+  - repo: local
     hooks:
       - id: local-biome-check
         name: biome check

Cargo.toml

@@ -21,30 +21,30 @@ categories = ["database-implementations"]
 rust-version = "1.78.0"
 
 [workspace.dependencies]
-lance = { "version" = "=0.23.2", "features" = ["dynamodb"] }
-lance-io = { version = "=0.23.2" }
-lance-index = { version = "=0.23.2" }
-lance-linalg = { version = "=0.23.2" }
-lance-table = { version = "=0.23.2" }
-lance-testing = { version = "=0.23.2" }
-lance-datafusion = { version = "=0.23.2" }
-lance-encoding = { version = "=0.23.2" }
+lance = { "version" = "=0.24.1", "features" = ["dynamodb"] }
+lance-io = { version = "=0.24.1" }
+lance-index = { version = "=0.24.1" }
+lance-linalg = { version = "=0.24.1" }
+lance-table = { version = "=0.24.1" }
+lance-testing = { version = "=0.24.1" }
+lance-datafusion = { version = "=0.24.1" }
+lance-encoding = { version = "=0.24.1" }
 # Note that this one does not include pyarrow
-arrow = { version = "53.2", optional = false }
-arrow-array = "53.2"
-arrow-data = "53.2"
-arrow-ipc = "53.2"
-arrow-ord = "53.2"
-arrow-schema = "53.2"
-arrow-arith = "53.2"
-arrow-cast = "53.2"
+arrow = { version = "54.1", optional = false }
+arrow-array = "54.1"
+arrow-data = "54.1"
+arrow-ipc = "54.1"
+arrow-ord = "54.1"
+arrow-schema = "54.1"
+arrow-arith = "54.1"
+arrow-cast = "54.1"
 async-trait = "0"
-datafusion = { version = "44.0", default-features = false }
-datafusion-catalog = "44.0"
-datafusion-common = { version = "44.0", default-features = false }
-datafusion-execution = "44.0"
-datafusion-expr = "44.0"
-datafusion-physical-plan = "44.0"
+datafusion = { version = "45.0", default-features = false }
+datafusion-catalog = "45.0"
+datafusion-common = { version = "45.0", default-features = false }
+datafusion-execution = "45.0"
+datafusion-expr = "45.0"
+datafusion-physical-plan = "45.0"
 env_logger = "0.11"
 half = { "version" = "=2.4.1", default-features = false, features = [
     "num-traits",
@@ -60,6 +60,7 @@ num-traits = "0.2"
 rand = "0.8"
 regex = "1.10"
 lazy_static = "1"
+semver = "1.0.25"
 
 # Temporary pins to work around downstream issues
 # https://github.com/apache/arrow-rs/commit/2fddf85afcd20110ce783ed5b4cdeb82293da30b

ci/parse_requirements.py

@@ -0,0 +1,41 @@
+import argparse
+import toml
+
+
+def parse_dependencies(pyproject_path, extras=None):
+    with open(pyproject_path, "r") as file:
+        pyproject = toml.load(file)
+
+    dependencies = pyproject.get("project", {}).get("dependencies", [])
+    for dependency in dependencies:
+        print(dependency)
+
+    optional_dependencies = pyproject.get("project", {}).get(
+        "optional-dependencies", {}
+    )
+
+    if extras:
+        for extra in extras.split(","):
+            for dep in optional_dependencies.get(extra, []):
+                print(dep)
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Generate requirements.txt from pyproject.toml"
+    )
+    parser.add_argument("path", type=str, help="Path to pyproject.toml")
+    parser.add_argument(
+        "--extras",
+        type=str,
+        help="Comma-separated list of extras to include",
+        default="",
+    )
+
+    args = parser.parse_args()
+
+    parse_dependencies(args.path, args.extras)
+
+
+if __name__ == "__main__":
+    main()

docs/mkdocs.yml

@@ -377,6 +377,7 @@ extra_css:
 
 extra_javascript:
   - "extra_js/init_ask_ai_widget.js"
+  - "extra_js/reo.js"
 
 extra:
   analytics:

docs/src/extra_js/reo.js

@@ -0,0 +1 @@
+!function(){var e,t,n;e="9627b71b382d201",t=function(){Reo.init({clientID:"9627b71b382d201"})},(n=document.createElement("script")).src="https://static.reo.dev/"+e+"/reo.js",n.defer=!0,n.onload=t,document.head.appendChild(n)}();

java/core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
         <groupId>com.lancedb</groupId>
         <artifactId>lancedb-parent</artifactId>
-        <version>0.16.1-beta.3</version>
+        <version>0.18.0-final.0</version>
         <relativePath>../pom.xml</relativePath>
     </parent>
 

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.16.1-beta.3</version>
+    <version>0.18.0-final.0</version>
     <packaging>pom</packaging>
 
     <name>LanceDB Parent</name>

node/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "vectordb",
-  "version": "0.16.1-beta.3",
+  "version": "0.18.0",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "vectordb",
-      "version": "0.16.1-beta.3",
+      "version": "0.18.0",
       "cpu": [
         "x64",
         "arm64"
@@ -52,14 +52,14 @@
         "uuid": "^9.0.0"
       },
       "optionalDependencies": {
-        "@lancedb/vectordb-darwin-arm64": "0.16.1-beta.3",
-        "@lancedb/vectordb-darwin-x64": "0.16.1-beta.3",
-        "@lancedb/vectordb-linux-arm64-gnu": "0.16.1-beta.3",
-        "@lancedb/vectordb-linux-arm64-musl": "0.16.1-beta.3",
-        "@lancedb/vectordb-linux-x64-gnu": "0.16.1-beta.3",
-        "@lancedb/vectordb-linux-x64-musl": "0.16.1-beta.3",
-        "@lancedb/vectordb-win32-arm64-msvc": "0.16.1-beta.3",
-        "@lancedb/vectordb-win32-x64-msvc": "0.16.1-beta.3"
+        "@lancedb/vectordb-darwin-arm64": "0.18.0",
+        "@lancedb/vectordb-darwin-x64": "0.18.0",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.18.0",
+        "@lancedb/vectordb-linux-arm64-musl": "0.18.0",
+        "@lancedb/vectordb-linux-x64-gnu": "0.18.0",
+        "@lancedb/vectordb-linux-x64-musl": "0.18.0",
+        "@lancedb/vectordb-win32-arm64-msvc": "0.18.0",
+        "@lancedb/vectordb-win32-x64-msvc": "0.18.0"
       },
       "peerDependencies": {
         "@apache-arrow/ts": "^14.0.2",
@@ -330,9 +330,9 @@
       }
     },
     "node_modules/@lancedb/vectordb-darwin-arm64": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.16.1-beta.3.tgz",
-      "integrity": "sha512-k2dfDNvoFjZuF8RCkFX9yFkLIg292mFg+o6IUeXndlikhABi8F+NbRODGUxJf3QUioks2tGF831KFoV5oQyeEA==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.18.0.tgz",
+      "integrity": "sha512-ormNCmny1j64aSZRrZeUQ1Zs8cOFKrW14NgTmW3AehDuru+Ep+8AriHA5Pmyi6raBOZfNzDSiZs/LTzzyVaa7g==",
       "cpu": [
         "arm64"
       ],
@@ -343,9 +343,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-darwin-x64": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.16.1-beta.3.tgz",
-      "integrity": "sha512-pYvwcAXBB3MXxa2kvK8PxMoEsaE+EFld5pky6dDo6qJQVepUz9pi/e1FTLxW6m0mgwtRj52P6xe55sj1Yln9Qw==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.18.0.tgz",
+      "integrity": "sha512-S4skQ1RXXQJciq40s84Kyy7v3YC+nao8pX4xUyxDcKRx+90Qg9eH+tehs6XLN1IjrQT/9CWKaE5wxZmv6Oys4g==",
       "cpu": [
         "x64"
       ],
@@ -356,9 +356,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-linux-arm64-gnu": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.16.1-beta.3.tgz",
-      "integrity": "sha512-BS4rnBtKGJlEdbYgOe85mGhviQaSfEXl8qw0fh0ml8E0qbi5RuLtwfTFMe3yAKSOnNAvaJISqXQyUN7hzkYkUQ==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.18.0.tgz",
+      "integrity": "sha512-1txr4tasVdxy321/4Fw8GJPjzrf84F02L9ffN8JebHmmR0S8uk2MKf2WsyLaSVRPd4YHIvvf3qmG0RGaUsb2sw==",
       "cpu": [
         "arm64"
       ],
@@ -369,9 +369,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-linux-arm64-musl": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-musl/-/vectordb-linux-arm64-musl-0.16.1-beta.3.tgz",
-      "integrity": "sha512-/F1mzpgSipfXjeaXJx5c0zLPOipPKnSPIpYviSdLU2Ahm1aHLweW1UsoiUoRkBkvEcVrZfHxL64vasey2I0P7Q==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-musl/-/vectordb-linux-arm64-musl-0.18.0.tgz",
+      "integrity": "sha512-8xS1xaoJeFDx6WmDBcfueWvIbdNX/ptQXfoC7hYICwNHizjlyt4O3Nxz8uG9URMF1y9saUYUditIHLzLVZc76g==",
       "cpu": [
         "arm64"
       ],
@@ -382,9 +382,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-linux-x64-gnu": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.16.1-beta.3.tgz",
-      "integrity": "sha512-zGn2Oby8GAQYG7+dqFVi2DDzli2/GAAY7lwPoYbPlyVytcdTlXRsxea1XiT1jzZmyKIlrxA/XXSRsmRq4n1j1w==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.18.0.tgz",
+      "integrity": "sha512-8XUc2UnEV3awv0DGJS5gRA7yTkicX6oPN7GudXXxycCKL33FJ2ah7hkeDia9Bhk9MmvTonvsEDvUSqnglcpqfA==",
       "cpu": [
         "x64"
       ],
@@ -395,9 +395,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-linux-x64-musl": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-musl/-/vectordb-linux-x64-musl-0.16.1-beta.3.tgz",
-      "integrity": "sha512-MXYvI7dL+0QtWGDuliUUaEp/XQN+hSndtDc8wlAMyI0lOzmTvC7/C3OZQcMKf6JISZuNS71OVzVTYDYSab9aXw==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-musl/-/vectordb-linux-x64-musl-0.18.0.tgz",
+      "integrity": "sha512-LV7TuWgLcL82Wdq+EH2Xs3+apqeLohwYLlVIauVAwKEHvdwyNxTOW9TaNLvHXcbylIh7agl2xXvASCNhYZAyzA==",
       "cpu": [
         "x64"
       ],
@@ -408,9 +408,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-win32-arm64-msvc": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-arm64-msvc/-/vectordb-win32-arm64-msvc-0.16.1-beta.3.tgz",
-      "integrity": "sha512-1dbUSg+Mi+0W8JAUXqNWC+uCr0RUqVHhxFVGLSlprqZ8qFJYQ61jFSZr4onOYj9Ta1n6tUb3Nc4acxf3vXXPmw==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-arm64-msvc/-/vectordb-win32-arm64-msvc-0.18.0.tgz",
+      "integrity": "sha512-kxdCnKfvnuDKoKZRUBbreMBpimHb+k9/pFR48GN6JSrIuzUDx5G1VjHKBmaFhbveZCOBjjtYlg/8ohnWQHZfeA==",
       "cpu": [
         "arm64"
       ],
@@ -421,9 +421,9 @@
       ]
     },
     "node_modules/@lancedb/vectordb-win32-x64-msvc": {
-      "version": "0.16.1-beta.3",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.16.1-beta.3.tgz",
-      "integrity": "sha512-K9oT47zKnFoCEB/JjVKG+w+L0GOMDsPPln+B2TvefAXAWrvweCN2H4LUdsBYCTnntzy80OJCwwH3OwX07M1Y3g==",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.18.0.tgz",
+      "integrity": "sha512-uAE80q50cAp4gHoGvclxJqZGqj3/9oN9kz8iXgNIxiPngqnN01kVyaj4ulm4Qk/nauWUhHJ3tjTh/+CpkhSc2Q==",
       "cpu": [
         "x64"
       ],

node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "vectordb",
-  "version": "0.16.1-beta.3",
+  "version": "0.18.0",
   "description": " Serverless, low-latency vector database for AI applications",
   "private": false,
   "main": "dist/index.js",
@@ -92,13 +92,13 @@
     }
   },
   "optionalDependencies": {
-    "@lancedb/vectordb-darwin-x64": "0.16.1-beta.3",
-    "@lancedb/vectordb-darwin-arm64": "0.16.1-beta.3",
-    "@lancedb/vectordb-linux-x64-gnu": "0.16.1-beta.3",
-    "@lancedb/vectordb-linux-arm64-gnu": "0.16.1-beta.3",
-    "@lancedb/vectordb-linux-x64-musl": "0.16.1-beta.3",
-    "@lancedb/vectordb-linux-arm64-musl": "0.16.1-beta.3",
-    "@lancedb/vectordb-win32-x64-msvc": "0.16.1-beta.3",
-    "@lancedb/vectordb-win32-arm64-msvc": "0.16.1-beta.3"
+    "@lancedb/vectordb-darwin-x64": "0.18.0",
+    "@lancedb/vectordb-darwin-arm64": "0.18.0",
+    "@lancedb/vectordb-linux-x64-gnu": "0.18.0",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.18.0",
+    "@lancedb/vectordb-linux-x64-musl": "0.18.0",
+    "@lancedb/vectordb-linux-arm64-musl": "0.18.0",
+    "@lancedb/vectordb-win32-x64-msvc": "0.18.0",
+    "@lancedb/vectordb-win32-arm64-msvc": "0.18.0"
   }
 }

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.16.1-beta.3"
+version = "0.18.0"
 license.workspace = true
 description.workspace = true
 repository.workspace = true

nodejs/__test__/s3_integration.test.ts

@@ -175,6 +175,8 @@ maybeDescribe("storage_options", () => {
 
     tableNames = await db.tableNames();
     expect(tableNames).toEqual([]);
+
+    await db.dropAllTables();
   });
 
   it("can configure encryption at connection and table level", async () => {
@@ -210,6 +212,8 @@ maybeDescribe("storage_options", () => {
     await table.add([{ a: 2, b: 3 }]);
 
     await bucket.assertAllEncrypted("test/table2.lance", kmsKey.keyId);
+
+    await db.dropAllTables();
   });
 });
 
@@ -298,5 +302,32 @@ maybeDescribe("DynamoDB Lock", () => {
 
     const rowCount = await table.countRows();
     expect(rowCount).toBe(6);
+
+    await db.dropAllTables();
+  });
+
+  it("clears dynamodb state after dropping all tables", async () => {
+    const uri = `s3+ddb://${bucket.name}/test?ddbTableName=${commitTable.name}`;
+    const db = await connect(uri, {
+      storageOptions: CONFIG,
+      readConsistencyInterval: 0,
+    });
+
+    await db.createTable("foo", [{ a: 1, b: 2 }]);
+    await db.createTable("bar", [{ a: 1, b: 2 }]);
+
+    let tableNames = await db.tableNames();
+    expect(tableNames).toEqual(["bar", "foo"]);
+
+    await db.dropAllTables();
+    tableNames = await db.tableNames();
+    expect(tableNames).toEqual([]);
+
+    // We can create a new table with the same name as the one we dropped.
+    await db.createTable("foo", [{ a: 1, b: 2 }]);
+    tableNames = await db.tableNames();
+    expect(tableNames).toEqual(["foo"]);
+
+    await db.dropAllTables();
   });
 });

nodejs/__test__/table.test.ts

@@ -666,11 +666,11 @@ describe("When creating an index", () => {
     expect(fs.readdirSync(indexDir)).toHaveLength(1);
 
     for await (const r of tbl.query().where("id > 1").select(["id"])) {
-      expect(r.numRows).toBe(10);
+      expect(r.numRows).toBe(298);
     }
     // should also work with 'filter' alias
     for await (const r of tbl.query().filter("id > 1").select(["id"])) {
-      expect(r.numRows).toBe(10);
+      expect(r.numRows).toBe(298);
     }
   });
 

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

nodejs/npm/darwin-x64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["darwin"],
 	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",

nodejs/npm/linux-arm64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",

nodejs/npm/linux-arm64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",

nodejs/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",

nodejs/npm/linux-x64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",

nodejs/npm/win32-arm64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.16.1-beta.3",
+  "version": "0.18.0",
   "os": [
     "win32"
   ],

nodejs/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.16.1-beta.3",
+	"version": "0.18.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "@lancedb/lancedb",
-  "version": "0.16.1-beta.3",
+  "version": "0.18.0",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "@lancedb/lancedb",
-      "version": "0.16.1-beta.3",
+      "version": "0.18.0",
       "cpu": [
         "x64",
         "arm64"

nodejs/package.json

@@ -11,7 +11,7 @@
     "ann"
   ],
   "private": false,
-  "version": "0.16.1-beta.3",
+  "version": "0.18.0",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

pyright_report.csv

@@ -0,0 +1,56 @@
+file,errors,warnings,total_issues
+python/python/lancedb/arrow.py,0,0,0
+python/python/lancedb/background_loop.py,0,0,0
+python/python/lancedb/embeddings/__init__.py,0,0,0
+python/python/lancedb/exceptions.py,0,0,0
+python/python/lancedb/index.py,0,0,0
+python/python/lancedb/integrations/__init__.py,0,0,0
+python/python/lancedb/remote/__init__.py,0,0,0
+python/python/lancedb/remote/errors.py,0,0,0
+python/python/lancedb/rerankers/__init__.py,0,0,0
+python/python/lancedb/rerankers/answerdotai.py,0,0,0
+python/python/lancedb/rerankers/cohere.py,0,0,0
+python/python/lancedb/rerankers/colbert.py,0,0,0
+python/python/lancedb/rerankers/cross_encoder.py,0,0,0
+python/python/lancedb/rerankers/openai.py,0,0,0
+python/python/lancedb/rerankers/util.py,0,0,0
+python/python/lancedb/rerankers/voyageai.py,0,0,0
+python/python/lancedb/schema.py,0,0,0
+python/python/lancedb/types.py,0,0,0
+python/python/lancedb/__init__.py,0,1,1
+python/python/lancedb/conftest.py,1,0,1
+python/python/lancedb/embeddings/bedrock.py,1,0,1
+python/python/lancedb/merge.py,1,0,1
+python/python/lancedb/rerankers/base.py,1,0,1
+python/python/lancedb/rerankers/jinaai.py,0,1,1
+python/python/lancedb/rerankers/linear_combination.py,1,0,1
+python/python/lancedb/embeddings/instructor.py,2,0,2
+python/python/lancedb/embeddings/openai.py,2,0,2
+python/python/lancedb/embeddings/watsonx.py,2,0,2
+python/python/lancedb/embeddings/registry.py,3,0,3
+python/python/lancedb/embeddings/sentence_transformers.py,3,0,3
+python/python/lancedb/integrations/pyarrow.py,3,0,3
+python/python/lancedb/rerankers/rrf.py,3,0,3
+python/python/lancedb/dependencies.py,4,0,4
+python/python/lancedb/embeddings/gemini_text.py,4,0,4
+python/python/lancedb/embeddings/gte.py,4,0,4
+python/python/lancedb/embeddings/gte_mlx_model.py,4,0,4
+python/python/lancedb/embeddings/ollama.py,4,0,4
+python/python/lancedb/embeddings/transformers.py,4,0,4
+python/python/lancedb/remote/db.py,5,0,5
+python/python/lancedb/context.py,6,0,6
+python/python/lancedb/embeddings/cohere.py,6,0,6
+python/python/lancedb/fts.py,6,0,6
+python/python/lancedb/db.py,9,0,9
+python/python/lancedb/embeddings/utils.py,9,0,9
+python/python/lancedb/common.py,11,0,11
+python/python/lancedb/util.py,13,0,13
+python/python/lancedb/embeddings/imagebind.py,14,0,14
+python/python/lancedb/embeddings/voyageai.py,15,0,15
+python/python/lancedb/embeddings/open_clip.py,16,0,16
+python/python/lancedb/pydantic.py,16,0,16
+python/python/lancedb/embeddings/base.py,17,0,17
+python/python/lancedb/embeddings/jinaai.py,18,1,19
+python/python/lancedb/remote/table.py,23,0,23
+python/python/lancedb/query.py,47,1,48
+python/python/lancedb/table.py,61,0,61

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.20.0"
+current_version = "0.21.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

python/CONTRIBUTING.md

@@ -8,9 +8,9 @@ For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).
 The Python package is a wrapper around the Rust library, `lancedb`. We use
 [pyo3](https://pyo3.rs/) to create the bindings between Rust and Python.
 
-* `src/`: Rust bindings source code
-* `python/lancedb`: Python package source code
-* `python/tests`: Unit tests
+- `src/`: Rust bindings source code
+- `python/lancedb`: Python package source code
+- `python/tests`: Unit tests
 
 ## Development environment
 
@@ -61,6 +61,12 @@ make test
 make doctest
 ```
 
+Run type checking:
+
+```shell
+make typecheck
+```
+
 To run a single test, you can use the `pytest` command directly. Provide the path
 to the test file, and optionally the test name after `::`.
 

python/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.20.0"
+version = "0.21.1"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true
@@ -14,21 +14,20 @@ name = "_lancedb"
 crate-type = ["cdylib"]
 
 [dependencies]
-arrow = { version = "53.2", features = ["pyarrow"] }
+arrow = { version = "54.1", features = ["pyarrow"] }
 lancedb = { path = "../rust/lancedb", default-features = false }
 env_logger.workspace = true
-pyo3 = { version = "0.22.2", features = [
-    "extension-module",
-    "abi3-py39",
-    "gil-refs"
+pyo3 = { version = "0.23", features = ["extension-module", "abi3-py39"] }
+pyo3-async-runtimes = { version = "0.23", features = [
+    "attributes",
+    "tokio-runtime",
 ] }
-pyo3-async-runtimes = { version = "0.22", features = ["attributes", "tokio-runtime"] }
 pin-project = "1.1.5"
 futures.workspace = true
 tokio = { version = "1.40", features = ["sync"] }
 
 [build-dependencies]
-pyo3-build-config = { version = "0.20.3", features = [
+pyo3-build-config = { version = "0.23", features = [
     "extension-module",
     "abi3-py39",
 ] }

python/Makefile

@@ -23,6 +23,10 @@ check:		## Check formatting and lints.
 fix:		## Fix python lints
 	ruff check python --fix
 
+.PHONY: typecheck
+typecheck:	## Run type checking with pyright.
+	pyright
+
 .PHONY: doctest
 doctest:	## Run documentation tests.
 	pytest --doctest-modules python/lancedb
@@ -30,3 +34,7 @@ doctest:	## Run documentation tests.
 .PHONY: test
 test:		## Run tests.
 	pytest python/tests -vv --durations=10 -m "not slow and not s3_test"
+
+.PHONY: clean
+clean:
+	rm -rf data

python/pyproject.toml

@@ -4,11 +4,12 @@ name = "lancedb"
 dynamic = ["version"]
 dependencies = [
     "deprecation",
-    "pylance~=0.23.2",
     "tqdm>=4.27.0",
+    "pyarrow>=14",
     "pydantic>=1.10",
     "packaging",
     "overrides>=0.7",
+    "pylance>=0.23.2",
 ]
 description = "lancedb"
 authors = [{ name = "LanceDB Devs", email = "dev@lancedb.com" }]
@@ -91,7 +92,7 @@ requires = ["maturin>=1.4"]
 build-backend = "maturin"
 
 [tool.ruff.lint]
-select = ["F", "E", "W", "G", "TCH", "PERF"]
+select = ["F", "E", "W", "G", "PERF"]
 
 [tool.pytest.ini_options]
 addopts = "--strict-markers --ignore-glob=lancedb/embeddings/*.py"
@@ -102,5 +103,28 @@ markers = [
 ]
 
 [tool.pyright]
-include = ["python/lancedb/table.py"]
+include = [
+    "python/lancedb/index.py",
+    "python/lancedb/rerankers/util.py",
+    "python/lancedb/rerankers/__init__.py",
+    "python/lancedb/rerankers/voyageai.py",
+    "python/lancedb/rerankers/jinaai.py",
+    "python/lancedb/rerankers/openai.py",
+    "python/lancedb/rerankers/cross_encoder.py",
+    "python/lancedb/rerankers/colbert.py",
+    "python/lancedb/rerankers/answerdotai.py",
+    "python/lancedb/rerankers/cohere.py",
+    "python/lancedb/arrow.py",
+    "python/lancedb/__init__.py",
+    "python/lancedb/types.py",
+    "python/lancedb/integrations/__init__.py",
+    "python/lancedb/exceptions.py",
+    "python/lancedb/background_loop.py",
+    "python/lancedb/schema.py",
+    "python/lancedb/remote/__init__.py",
+    "python/lancedb/remote/errors.py",
+    "python/lancedb/embeddings/__init__.py",
+    "python/lancedb/_lancedb.pyi",
+]
+exclude = ["python/tests/"]
 pythonVersion = "3.12"

python/python/lancedb/__init__.py

@@ -14,6 +14,7 @@ from ._lancedb import connect as lancedb_connect
 from .common import URI, sanitize_uri
 from .db import AsyncConnection, DBConnection, LanceDBConnection
 from .remote import ClientConfig
+from .remote.db import RemoteDBConnection
 from .schema import vector
 from .table import AsyncTable
 
@@ -86,8 +87,6 @@ def connect(
     conn : DBConnection
         A connection to a LanceDB database.
     """
-    from .remote.db import RemoteDBConnection
-
     if isinstance(uri, str) and uri.startswith("db://"):
         if api_key is None:
             api_key = os.environ.get("LANCEDB_API_KEY")

python/python/lancedb/_lancedb.pyi

@@ -3,6 +3,7 @@ from typing import Dict, List, Optional, Tuple, Any, Union, Literal
 import pyarrow as pa
 
 from .index import BTree, IvfFlat, IvfPq, Bitmap, LabelList, HnswPq, HnswSq, FTS
+from .remote import ClientConfig
 
 class Connection(object):
     uri: str
@@ -71,11 +72,15 @@ async def connect(
     region: Optional[str],
     host_override: Optional[str],
     read_consistency_interval: Optional[float],
+    client_config: Optional[Union[ClientConfig, Dict[str, Any]]],
+    storage_options: Optional[Dict[str, str]],
 ) -> Connection: ...
 
 class RecordBatchStream:
+    @property
     def schema(self) -> pa.Schema: ...
-    async def next(self) -> Optional[pa.RecordBatch]: ...
+    def __aiter__(self) -> "RecordBatchStream": ...
+    async def __anext__(self) -> pa.RecordBatch: ...
 
 class Query:
     def where(self, filter: str): ...
@@ -142,6 +147,10 @@ class CompactionStats:
     files_removed: int
     files_added: int
 
+class CleanupStats:
+    bytes_removed: int
+    old_versions: int
+
 class RemovalStats:
     bytes_removed: int
     old_versions_removed: int

python/python/lancedb/query.py

@@ -110,7 +110,7 @@ class Query(pydantic.BaseModel):
     full_text_query: Optional[Union[str, dict]] = None
 
     # top k results to return
-    k: int
+    k: Optional[int] = None
 
     # # metrics
     metric: str = "L2"
@@ -257,7 +257,7 @@ class LanceQueryBuilder(ABC):
 
     def __init__(self, table: "Table"):
         self._table = table
-        self._limit = 10
+        self._limit = None
         self._offset = 0
         self._columns = None
         self._where = None
@@ -370,8 +370,7 @@ class LanceQueryBuilder(ABC):
             The maximum number of results to return.
             The default query limit is 10 results.
             For ANN/KNN queries, you must specify a limit.
-            Entering 0, a negative number, or None will reset
-            the limit to the default value of 10.
+            For plain searches, all records are returned if limit not set.
             *WARNING* if you have a large dataset, setting
             the limit to a large number, e.g. the table size,
             can potentially result in reading a
@@ -595,6 +594,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
         fast_search: bool = False,
     ):
         super().__init__(table)
+        if self._limit is None:
+            self._limit = 10
         self._query = query
         self._distance_type = "L2"
         self._nprobes = 20
@@ -888,6 +889,8 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
         fts_columns: Union[str, List[str]] = [],
     ):
         super().__init__(table)
+        if self._limit is None:
+            self._limit = 10
         self._query = query
         self._phrase_query = False
         self.ordering_field_name = ordering_field_name
@@ -1055,7 +1058,7 @@ class LanceEmptyQueryBuilder(LanceQueryBuilder):
         query = Query(
             columns=self._columns,
             filter=self._where,
-            k=self._limit or 10,
+            k=self._limit,
             with_row_id=self._with_row_id,
             vector=[],
             # not actually respected in remote query

python/python/lancedb/remote/db.py

@@ -9,7 +9,8 @@ from typing import Any, Dict, Iterable, List, Optional, Union
 from urllib.parse import urlparse
 import warnings
 
-from lancedb import connect_async
+# Remove this import to fix circular dependency
+# from lancedb import connect_async
 from lancedb.remote import ClientConfig
 import pyarrow as pa
 from overrides import override
@@ -78,6 +79,9 @@ class RemoteDBConnection(DBConnection):
 
         self.client_config = client_config
 
+        # Import connect_async here to avoid circular import
+        from lancedb import connect_async
+
         self._conn = LOOP.run(
             connect_async(
                 db_url,

python/python/lancedb/table.py

@@ -5,6 +5,7 @@ from __future__ import annotations
 
 import asyncio
 import inspect
+import deprecation
 import warnings
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
@@ -24,16 +25,15 @@ from typing import (
 )
 from urllib.parse import urlparse
 
-import lance
+from . import __version__
 from lancedb.arrow import peek_reader
 from lancedb.background_loop import LOOP
-from .dependencies import _check_for_pandas
+from .dependencies import _check_for_hugging_face, _check_for_pandas
 import pyarrow as pa
 import pyarrow.compute as pc
 import pyarrow.fs as pa_fs
 import numpy as np
 from lance import LanceDataset
-from lance.dependencies import _check_for_hugging_face
 
 from .common import DATA, VEC, VECTOR_COLUMN_NAME
 from .embeddings import EmbeddingFunctionConfig, EmbeddingFunctionRegistry
@@ -66,24 +66,36 @@ from .index import lang_mapping
 
 
 if TYPE_CHECKING:
-    from ._lancedb import Table as LanceDBTable, OptimizeStats, CompactionStats
+    from ._lancedb import (
+        Table as LanceDBTable,
+        OptimizeStats,
+        CleanupStats,
+        CompactionStats,
+    )
     from .db import LanceDBConnection
     from .index import IndexConfig
-    from lance.dataset import CleanupStats, ReaderLike
     import pandas
     import PIL
+    from .types import (
+        QueryType,
+        OnBadVectorsType,
+        AddMode,
+        CreateMode,
+        VectorIndexType,
+        ScalarIndexType,
+        BaseTokenizerType,
+        DistanceType,
+    )
+
 
 pd = safe_import_pandas()
 pl = safe_import_polars()
 
-QueryType = Literal["vector", "fts", "hybrid", "auto"]
-
 
 def _into_pyarrow_reader(data) -> pa.RecordBatchReader:
-    if _check_for_hugging_face(data):
-        # Huggingface datasets
-        from lance.dependencies import datasets
+    from lancedb.dependencies import datasets
 
+    if _check_for_hugging_face(data):
         if isinstance(data, datasets.Dataset):
             schema = data.features.arrow_schema
             return pa.RecordBatchReader.from_batches(schema, data.data.to_batches())
@@ -175,7 +187,7 @@ def _sanitize_data(
     data: "DATA",
     target_schema: Optional[pa.Schema] = None,
     metadata: Optional[dict] = None,  # embedding metadata
-    on_bad_vectors: Literal["error", "drop", "fill", "null"] = "error",
+    on_bad_vectors: OnBadVectorsType = "error",
     fill_value: float = 0.0,
     *,
     allow_subschema: bool = False,
@@ -321,7 +333,7 @@ def sanitize_create_table(
     data,
     schema: Union[pa.Schema, LanceModel],
     metadata=None,
-    on_bad_vectors: str = "error",
+    on_bad_vectors: OnBadVectorsType = "error",
     fill_value: float = 0.0,
 ):
     if inspect.isclass(schema) and issubclass(schema, LanceModel):
@@ -573,9 +585,7 @@ class Table(ABC):
         accelerator: Optional[str] = None,
         index_cache_size: Optional[int] = None,
         *,
-        index_type: Literal[
-            "IVF_FLAT", "IVF_PQ", "IVF_HNSW_SQ", "IVF_HNSW_PQ"
-        ] = "IVF_PQ",
+        index_type: VectorIndexType = "IVF_PQ",
         num_bits: int = 8,
         max_iterations: int = 50,
         sample_rate: int = 256,
@@ -640,7 +650,7 @@ class Table(ABC):
         column: str,
         *,
         replace: bool = True,
-        index_type: Literal["BTREE", "BITMAP", "LABEL_LIST"] = "BTREE",
+        index_type: ScalarIndexType = "BTREE",
     ):
         """Create a scalar index on a column.
 
@@ -705,7 +715,7 @@ class Table(ABC):
         tokenizer_name: Optional[str] = None,
         with_position: bool = True,
         # tokenizer configs:
-        base_tokenizer: Literal["simple", "raw", "whitespace"] = "simple",
+        base_tokenizer: BaseTokenizerType = "simple",
         language: str = "English",
         max_token_length: Optional[int] = 40,
         lower_case: bool = True,
@@ -774,8 +784,8 @@ class Table(ABC):
     def add(
         self,
         data: DATA,
-        mode: str = "append",
-        on_bad_vectors: str = "error",
+        mode: AddMode = "append",
+        on_bad_vectors: OnBadVectorsType = "error",
         fill_value: float = 0.0,
     ):
         """Add more data to the [Table](Table).
@@ -957,7 +967,7 @@ class Table(ABC):
         self,
         merge: LanceMergeInsertBuilder,
         new_data: DATA,
-        on_bad_vectors: str,
+        on_bad_vectors: OnBadVectorsType,
         fill_value: float,
     ): ...
 
@@ -1074,7 +1084,7 @@ class Table(ABC):
         older_than: Optional[timedelta] = None,
         *,
         delete_unverified: bool = False,
-    ) -> CleanupStats:
+    ) -> "CleanupStats":
         """
         Clean up old versions of the table, freeing disk space.
 
@@ -1385,6 +1395,14 @@ class LanceTable(Table):
 
     def to_lance(self, **kwargs) -> LanceDataset:
         """Return the LanceDataset backing this table."""
+        try:
+            import lance
+        except ImportError:
+            raise ImportError(
+                "The lance library is required to use this function. "
+                "Please install with `pip install pylance`."
+            )
+
         return lance.dataset(
             self._dataset_path,
             version=self.version,
@@ -1561,10 +1579,10 @@ class LanceTable(Table):
 
     def create_index(
         self,
-        metric="L2",
+        metric: DistanceType = "l2",
         num_partitions=None,
         num_sub_vectors=None,
-        vector_column_name=VECTOR_COLUMN_NAME,
+        vector_column_name: str = VECTOR_COLUMN_NAME,
         replace: bool = True,
         accelerator: Optional[str] = None,
         index_cache_size: Optional[int] = None,
@@ -1650,7 +1668,7 @@ class LanceTable(Table):
         column: str,
         *,
         replace: bool = True,
-        index_type: Literal["BTREE", "BITMAP", "LABEL_LIST"] = "BTREE",
+        index_type: ScalarIndexType = "BTREE",
     ):
         if index_type == "BTREE":
             config = BTree()
@@ -1675,7 +1693,7 @@ class LanceTable(Table):
         tokenizer_name: Optional[str] = None,
         with_position: bool = True,
         # tokenizer configs:
-        base_tokenizer: str = "simple",
+        base_tokenizer: BaseTokenizerType = "simple",
         language: str = "English",
         max_token_length: Optional[int] = 40,
         lower_case: bool = True,
@@ -1809,8 +1827,8 @@ class LanceTable(Table):
     def add(
         self,
         data: DATA,
-        mode: str = "append",
-        on_bad_vectors: str = "error",
+        mode: AddMode = "append",
+        on_bad_vectors: OnBadVectorsType = "error",
         fill_value: float = 0.0,
     ):
         """Add data to the table.
@@ -1844,7 +1862,7 @@ class LanceTable(Table):
 
     def merge(
         self,
-        other_table: Union[LanceTable, ReaderLike],
+        other_table: Union[LanceTable, DATA],
         left_on: str,
         right_on: Optional[str] = None,
         schema: Optional[Union[pa.Schema, LanceModel]] = None,
@@ -1894,12 +1912,13 @@ class LanceTable(Table):
         1  2  b  e
         2  3  c  f
         """
-        if isinstance(schema, LanceModel):
-            schema = schema.to_arrow_schema()
         if isinstance(other_table, LanceTable):
             other_table = other_table.to_lance()
-        if isinstance(other_table, LanceDataset):
-            other_table = other_table.to_table()
+        else:
+            other_table = _sanitize_data(
+                other_table,
+                schema,
+            )
         self.to_lance().merge(
             other_table, left_on=left_on, right_on=right_on, schema=schema
         )
@@ -2047,7 +2066,7 @@ class LanceTable(Table):
             query_type,
             vector_column_name=vector_column_name,
             ordering_field_name=ordering_field_name,
-            fts_columns=fts_columns,
+            fts_columns=fts_columns or [],
         )
 
     @classmethod
@@ -2057,13 +2076,13 @@ class LanceTable(Table):
         name: str,
         data: Optional[DATA] = None,
         schema: Optional[pa.Schema] = None,
-        mode: Literal["create", "overwrite"] = "create",
+        mode: CreateMode = "create",
         exist_ok: bool = False,
-        on_bad_vectors: str = "error",
+        on_bad_vectors: OnBadVectorsType = "error",
         fill_value: float = 0.0,
         embedding_functions: Optional[List[EmbeddingFunctionConfig]] = None,
         *,
-        storage_options: Optional[Dict[str, str]] = None,
+        storage_options: Optional[Dict[str, str | bool]] = None,
         data_storage_version: Optional[str] = None,
         enable_v2_manifest_paths: Optional[bool] = None,
     ):
@@ -2217,17 +2236,22 @@ class LanceTable(Table):
         self,
         merge: LanceMergeInsertBuilder,
         new_data: DATA,
-        on_bad_vectors: str,
+        on_bad_vectors: OnBadVectorsType,
         fill_value: float,
     ):
         LOOP.run(self._table._do_merge(merge, new_data, on_bad_vectors, fill_value))
 
+    @deprecation.deprecated(
+        deprecated_in="0.21.0",
+        current_version=__version__,
+        details="Use `Table.optimize` instead.",
+    )
     def cleanup_old_versions(
         self,
         older_than: Optional[timedelta] = None,
         *,
         delete_unverified: bool = False,
-    ) -> CleanupStats:
+    ) -> "CleanupStats":
         """
         Clean up old versions of the table, freeing disk space.
 
@@ -2252,6 +2276,11 @@ class LanceTable(Table):
             older_than, delete_unverified=delete_unverified
         )
 
+    @deprecation.deprecated(
+        deprecated_in="0.21.0",
+        current_version=__version__,
+        details="Use `Table.optimize` instead.",
+    )
     def compact_files(self, *args, **kwargs) -> CompactionStats:
         """
         Run the compaction process on the table.
@@ -2383,6 +2412,19 @@ class LanceTable(Table):
         """
         LOOP.run(self._table.migrate_v2_manifest_paths())
 
+    def replace_field_metadata(self, field_name: str, new_metadata: Dict[str, str]):
+        """
+        Replace the metadata of a field in the schema
+
+        Parameters
+        ----------
+        field_name: str
+            The name of the field to replace the metadata for
+        new_metadata: dict
+            The new metadata to set
+        """
+        LOOP.run(self._table.replace_field_metadata(field_name, new_metadata))
+
 
 def _handle_bad_vectors(
     reader: pa.RecordBatchReader,
@@ -2845,7 +2887,7 @@ class AsyncTable:
         data: DATA,
         *,
         mode: Optional[Literal["append", "overwrite"]] = "append",
-        on_bad_vectors: Optional[str] = None,
+        on_bad_vectors: Optional[OnBadVectorsType] = None,
         fill_value: Optional[float] = None,
     ):
         """Add more data to the [Table](Table).
@@ -2951,7 +2993,7 @@ class AsyncTable:
     @overload
     async def search(
         self,
-        query: Optional[Union[str]] = None,
+        query: Optional[str] = None,
         vector_column_name: Optional[str] = None,
         query_type: Literal["auto"] = ...,
         ordering_field_name: Optional[str] = None,
@@ -2961,7 +3003,7 @@ class AsyncTable:
     @overload
     async def search(
         self,
-        query: Optional[Union[str]] = None,
+        query: Optional[str] = None,
         vector_column_name: Optional[str] = None,
         query_type: Literal["hybrid"] = ...,
         ordering_field_name: Optional[str] = None,
@@ -3005,7 +3047,7 @@ class AsyncTable:
         query_type: QueryType = "auto",
         ordering_field_name: Optional[str] = None,
         fts_columns: Optional[Union[str, List[str]]] = None,
-    ) -> AsyncQuery:
+    ) -> Union[AsyncHybridQuery | AsyncFTSQuery | AsyncVectorQuery]:
         """Create a search query to find the nearest neighbors
         of the given query vector. We currently support [vector search][search]
         and [full-text search][experimental-full-text-search].
@@ -3195,7 +3237,9 @@ class AsyncTable:
         # The sync remote table calls into this method, so we need to map the
         # query to the async version of the query and run that here. This is only
         # used for that code path right now.
-        async_query = self.query().limit(query.k)
+        async_query = self.query()
+        if query.k is not None:
+            async_query = async_query.limit(query.k)
         if query.offset > 0:
             async_query = async_query.offset(query.offset)
         if query.columns:
@@ -3242,7 +3286,7 @@ class AsyncTable:
         self,
         merge: LanceMergeInsertBuilder,
         new_data: DATA,
-        on_bad_vectors: str,
+        on_bad_vectors: OnBadVectorsType,
         fill_value: float,
     ):
         schema = await self.schema()
@@ -3611,6 +3655,21 @@ class AsyncTable:
         """
         await self._inner.migrate_manifest_paths_v2()
 
+    async def replace_field_metadata(
+        self, field_name: str, new_metadata: dict[str, str]
+    ):
+        """
+        Replace the metadata of a field in the schema
+
+        Parameters
+        ----------
+        field_name: str
+            The name of the field to replace the metadata for
+        new_metadata: dict
+            The new metadata to set
+        """
+        await self._inner.replace_field_metadata(field_name, new_metadata)
+
 
 @dataclass
 class IndexStatistics:

python/python/lancedb/types.py

@@ -0,0 +1,28 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+from typing import Literal
+
+# Query type literals
+QueryType = Literal["vector", "fts", "hybrid", "auto"]
+
+# Distance type literals
+DistanceType = Literal["l2", "cosine", "dot"]
+DistanceTypeWithHamming = Literal["l2", "cosine", "dot", "hamming"]
+
+# Vector handling literals
+OnBadVectorsType = Literal["error", "drop", "fill", "null"]
+
+# Mode literals
+AddMode = Literal["append", "overwrite"]
+CreateMode = Literal["create", "overwrite"]
+
+# Index type literals
+VectorIndexType = Literal["IVF_FLAT", "IVF_PQ", "IVF_HNSW_SQ", "IVF_HNSW_PQ"]
+ScalarIndexType = Literal["BTREE", "BITMAP", "LABEL_LIST"]
+IndexType = Literal[
+    "IVF_PQ", "IVF_HNSW_PQ", "IVF_HNSW_SQ", "FTS", "BTREE", "BITMAP", "LABEL_LIST"
+]
+
+# Tokenizer literals
+BaseTokenizerType = Literal["simple", "raw", "whitespace"]

python/python/tests/test_embeddings.py

@@ -419,17 +419,17 @@ def test_embedding_function_safe_model_dump(embedding_type):
 
     dumped_model = model.safe_model_dump()
 
-    assert all(
-        not k.startswith("_") for k in dumped_model.keys()
-    ), f"{embedding_type}: Dumped model contains keys starting with underscore"
+    assert all(not k.startswith("_") for k in dumped_model.keys()), (
+        f"{embedding_type}: Dumped model contains keys starting with underscore"
+    )
 
-    assert (
-        "max_retries" in dumped_model
-    ), f"{embedding_type}: Essential field 'max_retries' is missing from dumped model"
+    assert "max_retries" in dumped_model, (
+        f"{embedding_type}: Essential field 'max_retries' is missing from dumped model"
+    )
 
-    assert isinstance(
-        dumped_model, dict
-    ), f"{embedding_type}: Dumped model is not a dictionary"
+    assert isinstance(dumped_model, dict), (
+        f"{embedding_type}: Dumped model is not a dictionary"
+    )
 
     for key in model.__dict__:
         if key.startswith("_"):

python/python/tests/test_fts.py

@@ -174,6 +174,10 @@ def test_search_fts(table, use_tantivy):
     assert len(results) == 5
     assert len(results[0]) == 3  # id, text, _score
 
+    # Default limit of 10
+    results = table.search("puppy").select(["id", "text"]).to_list()
+    assert len(results) == 10
+
 
 @pytest.mark.asyncio
 async def test_fts_select_async(async_table):

python/python/tests/test_hybrid_query.py

@@ -129,6 +129,6 @@ def test_normalize_scores():
             if invert:
                 expected = pc.subtract(1.0, expected)
 
-            assert pc.equal(
-                result, expected
-            ), f"Expected {expected} but got {result} for invert={invert}"
+            assert pc.equal(result, expected), (
+                f"Expected {expected} but got {result} for invert={invert}"
+            )

python/python/tests/test_query.py

@@ -784,8 +784,7 @@ async def test_query_search_auto(mem_db_async: AsyncConnection):
     with pytest.raises(
         Exception,
         match=(
-            "Cannot perform full text search unless an INVERTED index has "
-            "been created"
+            "Cannot perform full text search unless an INVERTED index has been created"
         ),
     ):
         query = await (await tbl2.search("0.1")).to_arrow()

python/python/tests/test_remote_db.py

@@ -9,6 +9,7 @@ import json
 import threading
 from unittest.mock import MagicMock
 import uuid
+from packaging.version import Version
 
 import lancedb
 from lancedb.conftest import MockTextEmbeddingFunction
@@ -277,11 +278,12 @@ def test_table_create_indices():
 
 
 @contextlib.contextmanager
-def query_test_table(query_handler):
+def query_test_table(query_handler, *, server_version=Version("0.1.0")):
     def handler(request):
         if request.path == "/v1/table/test/describe/":
             request.send_response(200)
             request.send_header("Content-Type", "application/json")
+            request.send_header("phalanx-version", str(server_version))
             request.end_headers()
             request.wfile.write(b"{}")
         elif request.path == "/v1/table/test/query/":
@@ -388,17 +390,25 @@ def test_query_sync_maximal():
         )
 
 
-def test_query_sync_multiple_vectors():
+@pytest.mark.parametrize("server_version", [Version("0.1.0"), Version("0.2.0")])
+def test_query_sync_batch_queries(server_version):
     def handler(body):
         # TODO: we will add the ability to get the server version,
         # so that we can decide how to perform batch quires.
         vectors = body["vector"]
+        if server_version >= Version(
+            "0.2.0"
+        ):  # we can handle batch queries in single request since 0.2.0
+            assert len(vectors) == 2
             res = []
             for i, vector in enumerate(vectors):
                 res.append({"id": 1, "query_index": i})
             return pa.Table.from_pylist(res)
+        else:
+            assert len(vectors) == 3  # matching dim
+            return pa.table({"id": [1]})
 
-    with query_test_table(handler) as table:
+    with query_test_table(handler, server_version=server_version) as table:
         results = table.search([[1, 2, 3], [4, 5, 6]]).limit(1).to_list()
         assert len(results) == 2
         results.sort(key=lambda x: x["query_index"])

python/python/tests/test_rerankers.py

@@ -131,9 +131,9 @@ def _run_test_reranker(reranker, table, query, query_vector, schema):
         "represents the relevance of the result to the query & should "
         "be descending."
     )
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
 
     # Vector search setting
     result = (
@@ -143,9 +143,9 @@ def _run_test_reranker(reranker, table, query, query_vector, schema):
         .to_arrow()
     )
     assert len(result) == 30
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
     result_explicit = (
         table.search(query_vector, vector_column_name="vector")
         .rerank(reranker=reranker, query_string=query)
@@ -168,9 +168,9 @@ def _run_test_reranker(reranker, table, query, query_vector, schema):
         .to_arrow()
     )
     assert len(result) > 0
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
 
     # empty FTS results
     query = "abcxyz" * 100
@@ -185,9 +185,9 @@ def _run_test_reranker(reranker, table, query, query_vector, schema):
 
     # should return _relevance_score column
     assert "_relevance_score" in result.column_names
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
 
     # Multi-vector search setting
     rs1 = table.search(query, vector_column_name="vector").limit(10).with_row_id(True)
@@ -262,9 +262,9 @@ def _run_test_hybrid_reranker(reranker, tmp_path, use_tantivy):
         "represents the relevance of the result to the query & should "
         "be descending."
     )
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
 
     # Test with empty FTS results
     query = "abcxyz" * 100
@@ -278,9 +278,9 @@ def _run_test_hybrid_reranker(reranker, tmp_path, use_tantivy):
     )
     # should return _relevance_score column
     assert "_relevance_score" in result.column_names
-    assert np.all(
-        np.diff(result.column("_relevance_score").to_numpy()) <= 0
-    ), ascending_relevance_err
+    assert np.all(np.diff(result.column("_relevance_score").to_numpy()) <= 0), (
+        ascending_relevance_err
+    )
 
 
 @pytest.mark.parametrize("use_tantivy", [True, False])

python/python/tests/test_s3.py

@@ -252,3 +252,27 @@ def test_s3_dynamodb_sync(s3_bucket: str, commit_table: str, monkeypatch):
     db.drop_table("test_ddb_sync")
     assert db.table_names() == []
     db.drop_database()
+
+
+@pytest.mark.s3_test
+def test_s3_dynamodb_drop_all_tables(s3_bucket: str, commit_table: str, monkeypatch):
+    for key, value in CONFIG.items():
+        monkeypatch.setenv(key.upper(), value)
+
+    uri = f"s3+ddb://{s3_bucket}/test2?ddbTableName={commit_table}"
+    db = lancedb.connect(uri, read_consistency_interval=timedelta(0))
+    data = pa.table({"x": ["a", "b", "c"]})
+
+    db.create_table("foo", data)
+    db.create_table("bar", data)
+    assert db.table_names() == ["bar", "foo"]
+
+    # dropping all tables should clear multiple tables
+    db.drop_all_tables()
+    assert db.table_names() == []
+
+    # create a new table with the same name to ensure DDB is clean
+    db.create_table("foo", data)
+    assert db.table_names() == ["foo"]
+
+    db.drop_all_tables()

python/python/tests/test_table.py

@@ -1025,13 +1025,13 @@ def test_empty_query(mem_db: DBConnection):
 
     table = mem_db.create_table("my_table2", data=[{"id": i} for i in range(100)])
     df = table.search().select(["id"]).to_pandas()
-    assert len(df) == 10
+    assert len(df) == 100
     # None is the same as default
     df = table.search().select(["id"]).limit(None).to_pandas()
-    assert len(df) == 10
+    assert len(df) == 100
     # invalid limist is the same as None, wihch is the same as default
     df = table.search().select(["id"]).limit(-1).to_pandas()
-    assert len(df) == 10
+    assert len(df) == 100
     # valid limit should work
     df = table.search().select(["id"]).limit(42).to_pandas()
     assert len(df) == 42
@@ -1481,3 +1481,12 @@ async def test_optimize_delete_unverified(tmp_db_async: AsyncConnection, tmp_pat
         cleanup_older_than=timedelta(seconds=0), delete_unverified=True
     )
     assert stats.prune.old_versions_removed == 2
+
+
+def test_replace_field_metadata(tmp_path):
+    db = lancedb.connect(tmp_path)
+    table = db.create_table("my_table", data=[{"x": 0}])
+    table.replace_field_metadata("x", {"foo": "bar"})
+    schema = table.schema
+    field = schema[0].metadata
+    assert field == {b"foo": b"bar"}

python/src/error.rs

@@ -43,7 +43,7 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
                 } => Python::with_gil(|py| {
                     let message = err.to_string();
                     let http_err_cls = py
-                        .import_bound(intern!(py, "lancedb.remote.errors"))?
+                        .import(intern!(py, "lancedb.remote.errors"))?
                         .getattr(intern!(py, "HttpError"))?;
                     let err = http_err_cls.call1((
                         message,
@@ -63,7 +63,7 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
                         err.setattr(intern!(py, "__cause__"), cause_err)?;
                     }
 
-                    Err(PyErr::from_value_bound(err))
+                    Err(PyErr::from_value(err))
                 }),
                 LanceError::Retry {
                     request_id,
@@ -85,7 +85,7 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
 
                     let message = err.to_string();
                     let retry_error_cls = py
-                        .import_bound(intern!(py, "lancedb.remote.errors"))?
+                        .import(intern!(py, "lancedb.remote.errors"))?
                         .getattr("RetryError")?;
                     let err = retry_error_cls.call1((
                         message,
@@ -100,7 +100,7 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
                     ))?;
 
                     err.setattr(intern!(py, "__cause__"), cause_err)?;
-                    Err(PyErr::from_value_bound(err))
+                    Err(PyErr::from_value(err))
                 }),
                 _ => self.runtime_error(),
             },
@@ -127,18 +127,16 @@ fn http_from_rust_error(
     status_code: Option<u16>,
 ) -> PyResult<PyErr> {
     let message = err.to_string();
-    let http_err_cls = py
-        .import_bound("lancedb.remote.errors")?
-        .getattr("HttpError")?;
+    let http_err_cls = py.import("lancedb.remote.errors")?.getattr("HttpError")?;
     let py_err = http_err_cls.call1((message, request_id, status_code))?;
 
     // Reset the traceback since it doesn't provide additional information.
-    let py_err = py_err.call_method1(intern!(py, "with_traceback"), (PyNone::get_bound(py),))?;
+    let py_err = py_err.call_method1(intern!(py, "with_traceback"), (PyNone::get(py),))?;
 
     if let Some(cause) = err.source() {
         let cause_err = http_from_rust_error(py, cause, request_id, status_code)?;
         py_err.setattr(intern!(py, "__cause__"), cause_err)?;
     }
 
-    Ok(PyErr::from_value_bound(py_err))
+    Ok(PyErr::from_value(py_err))
 }

python/src/index.rs

@@ -7,29 +7,32 @@ use lancedb::index::{
     vector::{IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder},
     Index as LanceDbIndex,
 };
+use pyo3::types::PyStringMethods;
+use pyo3::IntoPyObject;
 use pyo3::{
     exceptions::{PyKeyError, PyValueError},
     intern, pyclass, pymethods,
     types::PyAnyMethods,
-    Bound, FromPyObject, IntoPy, PyAny, PyObject, PyResult, Python,
+    Bound, FromPyObject, PyAny, PyResult, Python,
 };
 
 use crate::util::parse_distance_type;
 
-pub fn class_name<'a>(ob: &'a Bound<'_, PyAny>) -> PyResult<&'a str> {
-    let full_name: &str = ob
+pub fn class_name(ob: &'_ Bound<'_, PyAny>) -> PyResult<String> {
+    let full_name = ob
         .getattr(intern!(ob.py(), "__class__"))?
-        .getattr(intern!(ob.py(), "__name__"))?
-        .extract()?;
+        .getattr(intern!(ob.py(), "__name__"))?;
+    let full_name = full_name.downcast()?.to_string_lossy();
+
     match full_name.rsplit_once('.') {
-        Some((_, name)) => Ok(name),
-        None => Ok(full_name),
+        Some((_, name)) => Ok(name.to_string()),
+        None => Ok(full_name.to_string()),
     }
 }
 
 pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<LanceDbIndex> {
     if let Some(source) = source {
-        match class_name(source)? {
+        match class_name(source)?.as_str() {
             "BTree" => Ok(LanceDbIndex::BTree(BTreeIndexBuilder::default())),
             "Bitmap" => Ok(LanceDbIndex::Bitmap(Default::default())),
             "LabelList" => Ok(LanceDbIndex::LabelList(Default::default())),
@@ -196,11 +199,11 @@ impl IndexConfig {
 
     // For backwards-compatibility with the old sync SDK, we also support getting
     // attributes via __getitem__.
-    pub fn __getitem__(&self, key: String, py: Python<'_>) -> PyResult<PyObject> {
+    pub fn __getitem__<'a>(&self, key: String, py: Python<'a>) -> PyResult<Bound<'a, PyAny>> {
         match key.as_str() {
-            "index_type" => Ok(self.index_type.clone().into_py(py)),
-            "columns" => Ok(self.columns.clone().into_py(py)),
-            "name" | "index_name" => Ok(self.name.clone().into_py(py)),
+            "index_type" => Ok(self.index_type.clone().into_pyobject(py)?.into_any()),
+            "columns" => Ok(self.columns.clone().into_pyobject(py)?.into_any()),
+            "name" | "index_name" => Ok(self.name.clone().into_pyobject(py)?.into_any()),
             _ => Err(PyKeyError::new_err(format!("Invalid key: {}", key))),
         }
     }

python/src/table.rs

@@ -10,12 +10,13 @@ use lancedb::table::{
     Table as LanceDbTable,
 };
 use pyo3::{
-    exceptions::{PyRuntimeError, PyValueError},
+    exceptions::{PyKeyError, PyRuntimeError, PyValueError},
     pyclass, pymethods,
     types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
-    Bound, FromPyObject, PyAny, PyRef, PyResult, Python, ToPyObject,
+    Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
+use std::collections::HashMap;
 
 use crate::{
     error::PythonErrorExt,
@@ -221,7 +222,7 @@ impl Table {
             let stats = inner.index_stats(&index_name).await.infer_error()?;
             if let Some(stats) = stats {
                 Python::with_gil(|py| {
-                    let dict = PyDict::new_bound(py);
+                    let dict = PyDict::new(py);
                     dict.set_item("num_indexed_rows", stats.num_indexed_rows)?;
                     dict.set_item("num_unindexed_rows", stats.num_unindexed_rows)?;
                     dict.set_item("index_type", stats.index_type.to_string())?;
@@ -234,7 +235,7 @@ impl Table {
                         dict.set_item("num_indices", num_indices)?;
                     }
 
-                    Ok(Some(dict.to_object(py)))
+                    Ok(Some(dict.unbind()))
                 })
             } else {
                 Ok(None)
@@ -265,7 +266,7 @@ impl Table {
                 versions
                     .iter()
                     .map(|v| {
-                        let dict = PyDict::new_bound(py);
+                        let dict = PyDict::new(py);
                         dict.set_item("version", v.version).unwrap();
                         dict.set_item(
                             "timestamp",
@@ -274,14 +275,13 @@ impl Table {
                         .unwrap();
 
                         let tup: Vec<(&String, &String)> = v.metadata.iter().collect();
-                        dict.set_item("metadata", tup.into_py_dict_bound(py))
-                            .unwrap();
-                        dict.to_object(py)
+                        dict.set_item("metadata", tup.into_py_dict(py)?).unwrap();
+                        Ok(dict.unbind())
                     })
-                    .collect::<Vec<_>>()
+                    .collect::<PyResult<Vec<_>>>()
             });
 
-            Ok(versions_as_dict)
+            versions_as_dict
         })
     }
 
@@ -486,6 +486,37 @@ impl Table {
             Ok(())
         })
     }
+
+    pub fn replace_field_metadata<'a>(
+        self_: PyRef<'a, Self>,
+        field_name: String,
+        metadata: &Bound<'_, PyDict>,
+    ) -> PyResult<Bound<'a, PyAny>> {
+        let mut new_metadata = HashMap::<String, String>::new();
+        for (column_name, value) in metadata.into_iter() {
+            let key: String = column_name.extract()?;
+            let value: String = value.extract()?;
+            new_metadata.insert(key, value);
+        }
+
+        let inner = self_.inner_ref()?.clone();
+        future_into_py(self_.py(), async move {
+            let native_tbl = inner
+                .as_native()
+                .ok_or_else(|| PyValueError::new_err("This cannot be run on a remote table"))?;
+            let schema = native_tbl.manifest().await.infer_error()?.schema;
+            let field = schema
+                .field(&field_name)
+                .ok_or_else(|| PyKeyError::new_err(format!("Field {} not found", field_name)))?;
+
+            native_tbl
+                .replace_field_metadata(vec![(field.id as u32, new_metadata)])
+                .await
+                .infer_error()?;
+
+            Ok(())
+        })
+    }
 }
 
 #[derive(FromPyObject)]

rust/ffi/node/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-node"
-version = "0.16.1-beta.3"
+version = "0.18.0"
 description = "Serverless, low-latency vector database for AI applications"
 license.workspace = true
 edition.workspace = true

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.16.1-beta.3"
+version = "0.18.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -70,6 +70,7 @@ candle-core = { version = "0.6.0", optional = true }
 candle-transformers = { version = "0.6.0", optional = true }
 candle-nn = { version = "0.6.0", optional = true }
 tokenizers = { version = "0.19.1", optional = true }
+semver = { workspace = true }
 
 # For a workaround, see workspace Cargo.toml
 crunchy.workspace = true
@@ -87,6 +88,7 @@ aws-config = { version = "1.0" }
 aws-smithy-runtime = { version = "1.3" }
 datafusion.workspace = true
 http-body = "1"                                        # Matching reqwest
+rstest = "0.23.0"
 
 
 [features]

rust/lancedb/src/arrow.rs

@@ -4,12 +4,14 @@
 use std::{pin::Pin, sync::Arc};
 
 pub use arrow_schema;
-use futures::{Stream, StreamExt};
+use datafusion_common::DataFusionError;
+use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
+use futures::{Stream, StreamExt, TryStreamExt};
 
 #[cfg(feature = "polars")]
 use {crate::polars_arrow_convertors, polars::frame::ArrowChunk, polars::prelude::DataFrame};
 
-use crate::error::Result;
+use crate::{error::Result, Error};
 
 /// An iterator of batches that also has a schema
 pub trait RecordBatchReader: Iterator<Item = Result<arrow_array::RecordBatch>> {
@@ -65,6 +67,20 @@ impl<I: lance::io::RecordBatchStream + 'static> From<I> for SendableRecordBatchS
     }
 }
 
+pub trait SendableRecordBatchStreamExt {
+    fn into_df_stream(self) -> datafusion_physical_plan::SendableRecordBatchStream;
+}
+
+impl SendableRecordBatchStreamExt for SendableRecordBatchStream {
+    fn into_df_stream(self) -> datafusion_physical_plan::SendableRecordBatchStream {
+        let schema = self.schema();
+        Box::pin(RecordBatchStreamAdapter::new(
+            schema,
+            self.map_err(|ldb_err| DataFusionError::External(ldb_err.into())),
+        ))
+    }
+}
+
 /// A simple RecordBatchStream formed from the two parts (stream + schema)
 #[pin_project::pin_project]
 pub struct SimpleRecordBatchStream<S: Stream<Item = Result<arrow_array::RecordBatch>>> {
@@ -101,7 +117,7 @@ impl<S: Stream<Item = Result<arrow_array::RecordBatch>>> RecordBatchStream
 /// used in methods like [`crate::connection::Connection::create_table`]
 /// or [`crate::table::Table::add`]
 pub trait IntoArrow {
-    /// Convert the data into an Arrow array
+    /// Convert the data into an iterator of Arrow batches
     fn into_arrow(self) -> Result<Box<dyn arrow_array::RecordBatchReader + Send>>;
 }
 
@@ -113,11 +129,38 @@ impl<T: arrow_array::RecordBatchReader + Send + 'static> IntoArrow for T {
     }
 }
 
+/// A trait for converting incoming data to Arrow asynchronously
+///
+/// Serves the same purpose as [`IntoArrow`], but for asynchronous data.
+///
+/// Note: Arrow has no async equivalent to RecordBatchReader and so
+pub trait IntoArrowStream {
+    /// Convert the data into a stream of Arrow batches
+    fn into_arrow(self) -> Result<SendableRecordBatchStream>;
+}
+
 impl<S: Stream<Item = Result<arrow_array::RecordBatch>>> SimpleRecordBatchStream<S> {
     pub fn new(stream: S, schema: Arc<arrow_schema::Schema>) -> Self {
         Self { schema, stream }
     }
 }
+
+impl IntoArrowStream for SendableRecordBatchStream {
+    fn into_arrow(self) -> Result<SendableRecordBatchStream> {
+        Ok(self)
+    }
+}
+
+impl IntoArrowStream for datafusion_physical_plan::SendableRecordBatchStream {
+    fn into_arrow(self) -> Result<SendableRecordBatchStream> {
+        let schema = self.schema();
+        let stream = self.map_err(|df_err| Error::Runtime {
+            message: df_err.to_string(),
+        });
+        Ok(Box::pin(SimpleRecordBatchStream::new(stream, schema)))
+    }
+}
+
 #[cfg(feature = "polars")]
 /// An iterator of record batches formed from a Polars DataFrame.
 pub struct PolarsDataFrameRecordBatchReader {

rust/lancedb/src/catalog.rs

@@ -0,0 +1,82 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Catalog implementation for managing databases
+
+pub mod listing;
+
+use std::collections::HashMap;
+use std::sync::Arc;
+
+use crate::database::Database;
+use crate::error::Result;
+use async_trait::async_trait;
+
+/// Request parameters for listing databases
+#[derive(Clone, Debug, Default)]
+pub struct DatabaseNamesRequest {
+    /// Start listing after this name (exclusive)
+    pub start_after: Option<String>,
+    /// Maximum number of names to return
+    pub limit: Option<u32>,
+}
+
+/// Request to open an existing database
+#[derive(Clone, Debug)]
+pub struct OpenDatabaseRequest {
+    /// The name of the database to open
+    pub name: String,
+    /// A map of database-specific options
+    ///
+    /// Consult the catalog / database implementation to determine which options are available
+    pub database_options: HashMap<String, String>,
+}
+
+/// Database creation mode
+///
+/// The default behavior is Create
+pub enum CreateDatabaseMode {
+    /// Create new database, error if exists
+    Create,
+    /// Open existing database if present
+    ExistOk,
+    /// Overwrite existing database
+    Overwrite,
+}
+
+impl Default for CreateDatabaseMode {
+    fn default() -> Self {
+        Self::Create
+    }
+}
+
+/// Request to create a new database
+pub struct CreateDatabaseRequest {
+    /// The name of the database to create
+    pub name: String,
+    /// The creation mode
+    pub mode: CreateDatabaseMode,
+    /// A map of catalog-specific options, consult your catalog implementation to determine what's available
+    pub options: HashMap<String, String>,
+}
+
+#[async_trait]
+pub trait Catalog: Send + Sync + std::fmt::Debug + 'static {
+    /// List database names with pagination
+    async fn database_names(&self, request: DatabaseNamesRequest) -> Result<Vec<String>>;
+
+    /// Create a new database
+    async fn create_database(&self, request: CreateDatabaseRequest) -> Result<Arc<dyn Database>>;
+
+    /// Open existing database
+    async fn open_database(&self, request: OpenDatabaseRequest) -> Result<Arc<dyn Database>>;
+
+    /// Rename database
+    async fn rename_database(&self, old_name: &str, new_name: &str) -> Result<()>;
+
+    /// Delete database
+    async fn drop_database(&self, name: &str) -> Result<()>;
+
+    /// Delete all databases
+    async fn drop_all_databases(&self) -> Result<()>;
+}

rust/lancedb/src/catalog/listing.rs

@@ -0,0 +1,569 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Catalog implementation based on a local file system.
+
+use std::collections::HashMap;
+use std::fs::create_dir_all;
+use std::path::Path;
+use std::sync::Arc;
+
+use super::{
+    Catalog, CreateDatabaseMode, CreateDatabaseRequest, DatabaseNamesRequest, OpenDatabaseRequest,
+};
+use crate::connection::ConnectRequest;
+use crate::database::listing::ListingDatabase;
+use crate::database::Database;
+use crate::error::{CreateDirSnafu, Error, Result};
+use async_trait::async_trait;
+use lance::io::{ObjectStore, ObjectStoreParams, ObjectStoreRegistry};
+use lance_io::local::to_local_path;
+use object_store::path::Path as ObjectStorePath;
+use snafu::ResultExt;
+
+/// A catalog implementation that works by listing subfolders in a directory
+///
+/// The listing catalog will be created with a base folder specified by the URI.  Every subfolder
+/// in this base folder will be considered a database.  These will be opened as a
+/// [`crate::database::listing::ListingDatabase`]
+#[derive(Debug)]
+pub struct ListingCatalog {
+    object_store: ObjectStore,
+
+    uri: String,
+
+    base_path: ObjectStorePath,
+
+    storage_options: HashMap<String, String>,
+}
+
+impl ListingCatalog {
+    /// Try to create a local directory to store the lancedb dataset
+    pub fn try_create_dir(path: &str) -> core::result::Result<(), std::io::Error> {
+        let path = Path::new(path);
+        if !path.try_exists()? {
+            create_dir_all(path)?;
+        }
+        Ok(())
+    }
+
+    pub fn uri(&self) -> &str {
+        &self.uri
+    }
+
+    async fn open_path(path: &str) -> Result<Self> {
+        let (object_store, base_path) = ObjectStore::from_path(path).unwrap();
+        if object_store.is_local() {
+            Self::try_create_dir(path).context(CreateDirSnafu { path })?;
+        }
+
+        Ok(Self {
+            uri: path.to_string(),
+            base_path,
+            object_store,
+            storage_options: HashMap::new(),
+        })
+    }
+
+    pub async fn connect(request: &ConnectRequest) -> Result<Self> {
+        let uri = &request.uri;
+        let parse_res = url::Url::parse(uri);
+
+        match parse_res {
+            Ok(url) if url.scheme().len() == 1 && cfg!(windows) => Self::open_path(uri).await,
+            Ok(url) => {
+                let plain_uri = url.to_string();
+
+                let registry = Arc::new(ObjectStoreRegistry::default());
+                let storage_options = request.storage_options.clone();
+                let os_params = ObjectStoreParams {
+                    storage_options: Some(storage_options.clone()),
+                    ..Default::default()
+                };
+                let (object_store, base_path) =
+                    ObjectStore::from_uri_and_params(registry, &plain_uri, &os_params).await?;
+                if object_store.is_local() {
+                    Self::try_create_dir(&plain_uri).context(CreateDirSnafu { path: plain_uri })?;
+                }
+
+                Ok(Self {
+                    uri: String::from(url.clone()),
+                    base_path,
+                    object_store,
+                    storage_options,
+                })
+            }
+            Err(_) => Self::open_path(uri).await,
+        }
+    }
+
+    fn database_path(&self, name: &str) -> ObjectStorePath {
+        self.base_path.child(name.replace('\\', "/"))
+    }
+}
+
+#[async_trait]
+impl Catalog for ListingCatalog {
+    async fn database_names(&self, request: DatabaseNamesRequest) -> Result<Vec<String>> {
+        let mut f = self
+            .object_store
+            .read_dir(self.base_path.clone())
+            .await?
+            .iter()
+            .map(Path::new)
+            .filter_map(|p| p.file_name().and_then(|s| s.to_str().map(String::from)))
+            .collect::<Vec<String>>();
+        f.sort();
+
+        if let Some(start_after) = request.start_after {
+            let index = f
+                .iter()
+                .position(|name| name.as_str() > start_after.as_str())
+                .unwrap_or(f.len());
+            f.drain(0..index);
+        }
+        if let Some(limit) = request.limit {
+            f.truncate(limit as usize);
+        }
+        Ok(f)
+    }
+
+    async fn create_database(&self, request: CreateDatabaseRequest) -> Result<Arc<dyn Database>> {
+        let db_path = self.database_path(&request.name);
+        let db_path_str = to_local_path(&db_path);
+        let exists = Path::new(&db_path_str).exists();
+
+        match request.mode {
+            CreateDatabaseMode::Create if exists => {
+                return Err(Error::DatabaseAlreadyExists { name: request.name })
+            }
+            CreateDatabaseMode::Create => {
+                create_dir_all(db_path.to_string()).unwrap();
+            }
+            CreateDatabaseMode::ExistOk => {
+                if !exists {
+                    create_dir_all(db_path.to_string()).unwrap();
+                }
+            }
+            CreateDatabaseMode::Overwrite => {
+                if exists {
+                    self.drop_database(&request.name).await?;
+                }
+                create_dir_all(db_path.to_string()).unwrap();
+            }
+        }
+
+        let db_uri = format!("/{}/{}", self.base_path, request.name);
+
+        let connect_request = ConnectRequest {
+            uri: db_uri,
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            read_consistency_interval: None,
+            storage_options: self.storage_options.clone(),
+        };
+
+        Ok(Arc::new(
+            ListingDatabase::connect_with_options(&connect_request).await?,
+        ))
+    }
+
+    async fn open_database(&self, request: OpenDatabaseRequest) -> Result<Arc<dyn Database>> {
+        let db_path = self.database_path(&request.name);
+
+        let db_path_str = to_local_path(&db_path);
+        let exists = Path::new(&db_path_str).exists();
+        if !exists {
+            return Err(Error::DatabaseNotFound { name: request.name });
+        }
+
+        let connect_request = ConnectRequest {
+            uri: db_path.to_string(),
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            read_consistency_interval: None,
+            storage_options: self.storage_options.clone(),
+        };
+
+        Ok(Arc::new(
+            ListingDatabase::connect_with_options(&connect_request).await?,
+        ))
+    }
+
+    async fn rename_database(&self, _old_name: &str, _new_name: &str) -> Result<()> {
+        Err(Error::NotSupported {
+            message: "rename_database is not supported in LanceDB OSS yet".to_string(),
+        })
+    }
+
+    async fn drop_database(&self, name: &str) -> Result<()> {
+        let db_path = self.database_path(name);
+        self.object_store
+            .remove_dir_all(db_path.clone())
+            .await
+            .map_err(|err| match err {
+                lance::Error::NotFound { .. } => Error::DatabaseNotFound {
+                    name: name.to_owned(),
+                },
+                _ => Error::from(err),
+            })?;
+
+        Ok(())
+    }
+
+    async fn drop_all_databases(&self) -> Result<()> {
+        self.object_store
+            .remove_dir_all(self.base_path.clone())
+            .await?;
+        Ok(())
+    }
+}
+
+#[cfg(all(test, not(windows)))]
+mod tests {
+    use super::*;
+
+    /// file:/// URIs with drive letters do not work correctly on Windows
+    #[cfg(windows)]
+    fn path_to_uri(path: PathBuf) -> String {
+        path.to_str().unwrap().to_string()
+    }
+
+    #[cfg(not(windows))]
+    fn path_to_uri(path: PathBuf) -> String {
+        Url::from_file_path(path).unwrap().to_string()
+    }
+
+    async fn setup_catalog() -> (TempDir, ListingCatalog) {
+        let tempdir = tempfile::tempdir().unwrap();
+        let catalog_path = tempdir.path().join("catalog");
+        std::fs::create_dir_all(&catalog_path).unwrap();
+
+        let uri = path_to_uri(catalog_path);
+
+        let request = ConnectRequest {
+            uri: uri.clone(),
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            storage_options: HashMap::new(),
+            read_consistency_interval: None,
+        };
+
+        let catalog = ListingCatalog::connect(&request).await.unwrap();
+
+        (tempdir, catalog)
+    }
+
+    use crate::database::{CreateTableData, CreateTableRequest, TableNamesRequest};
+    use crate::table::TableDefinition;
+    use arrow_schema::Field;
+    use std::path::PathBuf;
+    use std::sync::Arc;
+    use tempfile::{tempdir, TempDir};
+    use url::Url;
+
+    #[tokio::test]
+    async fn test_database_names() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(names.is_empty());
+    }
+
+    #[tokio::test]
+    async fn test_create_database() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db1".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert_eq!(names, vec!["db1"]);
+    }
+
+    #[tokio::test]
+    async fn test_create_database_exist_ok() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        let db1 = catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db_exist_ok".into(),
+                mode: CreateDatabaseMode::ExistOk,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+        let dummy_schema = Arc::new(arrow_schema::Schema::new(Vec::<Field>::default()));
+        db1.create_table(CreateTableRequest {
+            name: "test_table".parse().unwrap(),
+            data: CreateTableData::Empty(TableDefinition::new_from_schema(dummy_schema)),
+            mode: Default::default(),
+            write_options: Default::default(),
+        })
+        .await
+        .unwrap();
+
+        let db2 = catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db_exist_ok".into(),
+                mode: CreateDatabaseMode::ExistOk,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let tables = db2.table_names(TableNamesRequest::default()).await.unwrap();
+        assert_eq!(tables, vec!["test_table".to_string()]);
+    }
+
+    #[tokio::test]
+    async fn test_create_database_overwrite() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        let db = catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db_overwrite".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+        let dummy_schema = Arc::new(arrow_schema::Schema::new(Vec::<Field>::default()));
+        db.create_table(CreateTableRequest {
+            name: "old_table".parse().unwrap(),
+            data: CreateTableData::Empty(TableDefinition::new_from_schema(dummy_schema)),
+            mode: Default::default(),
+            write_options: Default::default(),
+        })
+        .await
+        .unwrap();
+        let tables = db.table_names(TableNamesRequest::default()).await.unwrap();
+        assert!(!tables.is_empty());
+
+        let new_db = catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db_overwrite".into(),
+                mode: CreateDatabaseMode::Overwrite,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let tables = new_db
+            .table_names(TableNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(tables.is_empty());
+    }
+
+    #[tokio::test]
+    async fn test_create_database_overwrite_non_existing() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "new_db".into(),
+                mode: CreateDatabaseMode::Overwrite,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(names.contains(&"new_db".to_string()));
+    }
+
+    #[tokio::test]
+    async fn test_open_database() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        // Test open non-existent
+        let result = catalog
+            .open_database(OpenDatabaseRequest {
+                name: "missing".into(),
+                database_options: HashMap::new(),
+            })
+            .await;
+        assert!(matches!(
+            result.unwrap_err(),
+            Error::DatabaseNotFound { name } if name == "missing"
+        ));
+
+        // Create and open
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "valid_db".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let db = catalog
+            .open_database(OpenDatabaseRequest {
+                name: "valid_db".into(),
+                database_options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+        assert_eq!(
+            db.table_names(TableNamesRequest::default()).await.unwrap(),
+            Vec::<String>::new()
+        );
+    }
+
+    #[tokio::test]
+    async fn test_drop_database() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        // Create test database
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "to_drop".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(!names.is_empty());
+
+        // Drop database
+        catalog.drop_database("to_drop").await.unwrap();
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(names.is_empty());
+    }
+
+    #[tokio::test]
+    async fn test_drop_all_databases() {
+        let (_tempdir, catalog) = setup_catalog().await;
+
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db1".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+        catalog
+            .create_database(CreateDatabaseRequest {
+                name: "db2".into(),
+                mode: CreateDatabaseMode::Create,
+                options: HashMap::new(),
+            })
+            .await
+            .unwrap();
+
+        catalog.drop_all_databases().await.unwrap();
+
+        let names = catalog
+            .database_names(DatabaseNamesRequest::default())
+            .await
+            .unwrap();
+        assert!(names.is_empty());
+    }
+
+    #[tokio::test]
+    async fn test_rename_database_unsupported() {
+        let (_tempdir, catalog) = setup_catalog().await;
+        let result = catalog.rename_database("old", "new").await;
+        assert!(matches!(
+            result.unwrap_err(),
+            Error::NotSupported { message } if message.contains("rename_database")
+        ));
+    }
+
+    #[tokio::test]
+    async fn test_connect_local_path() {
+        let tmp_dir = tempdir().unwrap();
+        let path = tmp_dir.path().to_str().unwrap();
+
+        let request = ConnectRequest {
+            uri: path.to_string(),
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            storage_options: HashMap::new(),
+            read_consistency_interval: None,
+        };
+
+        let catalog = ListingCatalog::connect(&request).await.unwrap();
+        assert!(catalog.object_store.is_local());
+        assert_eq!(catalog.uri, path);
+    }
+
+    #[tokio::test]
+    async fn test_connect_file_scheme() {
+        let tmp_dir = tempdir().unwrap();
+        let path = tmp_dir.path();
+        let uri = path_to_uri(path.to_path_buf());
+
+        let request = ConnectRequest {
+            uri: uri.clone(),
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            storage_options: HashMap::new(),
+            read_consistency_interval: None,
+        };
+
+        let catalog = ListingCatalog::connect(&request).await.unwrap();
+        assert!(catalog.object_store.is_local());
+        assert_eq!(catalog.uri, uri);
+    }
+
+    #[tokio::test]
+    async fn test_connect_invalid_uri_fallback() {
+        let invalid_uri = "invalid:///path";
+        let request = ConnectRequest {
+            uri: invalid_uri.to_string(),
+            api_key: None,
+            region: None,
+            host_override: None,
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            storage_options: HashMap::new(),
+            read_consistency_interval: None,
+        };
+
+        let result = ListingCatalog::connect(&request).await;
+        assert!(result.is_err());
+    }
+}

rust/lancedb/src/connection.rs

@@ -11,7 +11,7 @@ use arrow_schema::{Field, SchemaRef};
 use lance::dataset::ReadParams;
 use object_store::aws::AwsCredential;
 
-use crate::arrow::IntoArrow;
+use crate::arrow::{IntoArrow, IntoArrowStream, SendableRecordBatchStream};
 use crate::database::listing::{
     ListingDatabase, OPT_NEW_TABLE_STORAGE_VERSION, OPT_NEW_TABLE_V2_MANIFEST_PATHS,
 };
@@ -75,6 +75,14 @@ impl IntoArrow for NoData {
     }
 }
 
+// Stores the value given from the initial CreateTableBuilder::new call
+// and defers errors until `execute` is called
+enum CreateTableBuilderInitialData {
+    None,
+    Iterator(Result<Box<dyn RecordBatchReader + Send>>),
+    Stream(Result<SendableRecordBatchStream>),
+}
+
 /// A builder for configuring a [`Connection::create_table`] operation
 pub struct CreateTableBuilder<const HAS_DATA: bool> {
     parent: Arc<dyn Database>,
@@ -83,7 +91,7 @@ pub struct CreateTableBuilder<const HAS_DATA: bool> {
     request: CreateTableRequest,
     // This is a bit clumsy but we defer errors until `execute` is called
     // to maintain backwards compatibility
-    data: Option<Result<Box<dyn RecordBatchReader + Send>>>,
+    data: CreateTableBuilderInitialData,
 }
 
 // Builder methods that only apply when we have initial data
@@ -103,7 +111,26 @@ impl CreateTableBuilder<true> {
             ),
             embeddings: Vec::new(),
             embedding_registry,
-            data: Some(data.into_arrow()),
+            data: CreateTableBuilderInitialData::Iterator(data.into_arrow()),
+        }
+    }
+
+    fn new_streaming<T: IntoArrowStream>(
+        parent: Arc<dyn Database>,
+        name: String,
+        data: T,
+        embedding_registry: Arc<dyn EmbeddingRegistry>,
+    ) -> Self {
+        let dummy_schema = Arc::new(arrow_schema::Schema::new(Vec::<Field>::default()));
+        Self {
+            parent,
+            request: CreateTableRequest::new(
+                name,
+                CreateTableData::Empty(TableDefinition::new_from_schema(dummy_schema)),
+            ),
+            embeddings: Vec::new(),
+            embedding_registry,
+            data: CreateTableBuilderInitialData::Stream(data.into_arrow()),
         }
     }
 
@@ -125,18 +152,38 @@ impl CreateTableBuilder<true> {
     }
 
     fn into_request(self) -> Result<CreateTableRequest> {
-        let data = if self.embeddings.is_empty() {
-            self.data.unwrap()?
-        } else {
-            let data = self.data.unwrap()?;
-            Box::new(WithEmbeddings::new(data, self.embeddings))
-        };
-        let req = self.request;
+        if self.embeddings.is_empty() {
+            match self.data {
+                CreateTableBuilderInitialData::Iterator(maybe_iter) => {
+                    let data = maybe_iter?;
                     Ok(CreateTableRequest {
                         data: CreateTableData::Data(data),
-            ..req
+                        ..self.request
                     })
                 }
+                CreateTableBuilderInitialData::None => {
+                    unreachable!("No data provided for CreateTableBuilder<true>")
+                }
+                CreateTableBuilderInitialData::Stream(maybe_stream) => {
+                    let data = maybe_stream?;
+                    Ok(CreateTableRequest {
+                        data: CreateTableData::StreamingData(data),
+                        ..self.request
+                    })
+                }
+            }
+        } else {
+            let CreateTableBuilderInitialData::Iterator(maybe_iter) = self.data else {
+                return Err(Error::NotSupported { message: "Creating a table with embeddings is currently not support when the input is streaming".to_string() });
+            };
+            let data = maybe_iter?;
+            let data = Box::new(WithEmbeddings::new(data, self.embeddings));
+            Ok(CreateTableRequest {
+                data: CreateTableData::Data(data),
+                ..self.request
+            })
+        }
+    }
 }
 
 // Builder methods that only apply when we do not have initial data
@@ -151,7 +198,7 @@ impl CreateTableBuilder<false> {
         Self {
             parent,
             request: CreateTableRequest::new(name, CreateTableData::Empty(table_definition)),
-            data: None,
+            data: CreateTableBuilderInitialData::None,
             embeddings: Vec::default(),
             embedding_registry,
         }
@@ -432,7 +479,7 @@ impl Connection {
         TableNamesBuilder::new(self.internal.clone())
     }
 
-    /// Create a new table from data
+    /// Create a new table from an iterator of data
     ///
     /// # Parameters
     ///
@@ -451,6 +498,25 @@ impl Connection {
         )
     }
 
+    /// Create a new table from a stream of data
+    ///
+    /// # Parameters
+    ///
+    /// * `name` - The name of the table
+    /// * `initial_data` - The initial data to write to the table
+    pub fn create_table_streaming<T: IntoArrowStream>(
+        &self,
+        name: impl Into<String>,
+        initial_data: T,
+    ) -> CreateTableBuilder<true> {
+        CreateTableBuilder::<true>::new_streaming(
+            self.internal.clone(),
+            name.into(),
+            initial_data,
+            self.embedding_registry.clone(),
+        )
+    }
+
     /// Create an empty table with a given schema
     ///
     /// # Parameters
@@ -788,12 +854,16 @@ mod test_utils {
 mod tests {
     use std::fs::create_dir_all;
 
+    use arrow::compute::concat_batches;
     use arrow_array::RecordBatchReader;
     use arrow_schema::{DataType, Field, Schema};
-    use futures::TryStreamExt;
+    use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
+    use futures::{stream, TryStreamExt};
+    use lance::error::{ArrowResult, DataFusionResult};
     use lance_testing::datagen::{BatchGenerator, IncrementingInt32};
     use tempfile::tempdir;
 
+    use crate::arrow::SimpleRecordBatchStream;
     use crate::database::listing::{ListingDatabaseOptions, NewTableConfig};
     use crate::query::QueryBase;
     use crate::query::{ExecutableQuery, QueryExecutionOptions};
@@ -976,6 +1046,63 @@ mod tests {
         assert_eq!(batches.len(), 1);
     }
 
+    #[tokio::test]
+    async fn test_create_table_streaming() {
+        let tmp_dir = tempdir().unwrap();
+
+        let uri = tmp_dir.path().to_str().unwrap();
+        let db = connect(uri).execute().await.unwrap();
+
+        let batches = make_data().collect::<ArrowResult<Vec<_>>>().unwrap();
+
+        let schema = batches.first().unwrap().schema();
+        let one_batch = concat_batches(&schema, batches.iter()).unwrap();
+
+        let ldb_stream = stream::iter(batches.clone().into_iter().map(Result::Ok));
+        let ldb_stream: SendableRecordBatchStream =
+            Box::pin(SimpleRecordBatchStream::new(ldb_stream, schema.clone()));
+
+        let tbl1 = db
+            .create_table_streaming("one", ldb_stream)
+            .execute()
+            .await
+            .unwrap();
+
+        let df_stream = stream::iter(batches.into_iter().map(DataFusionResult::Ok));
+        let df_stream: datafusion_physical_plan::SendableRecordBatchStream =
+            Box::pin(RecordBatchStreamAdapter::new(schema.clone(), df_stream));
+
+        let tbl2 = db
+            .create_table_streaming("two", df_stream)
+            .execute()
+            .await
+            .unwrap();
+
+        let tbl1_data = tbl1
+            .query()
+            .execute()
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+
+        let tbl1_data = concat_batches(&schema, tbl1_data.iter()).unwrap();
+        assert_eq!(tbl1_data, one_batch);
+
+        let tbl2_data = tbl2
+            .query()
+            .execute()
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+
+        let tbl2_data = concat_batches(&schema, tbl2_data.iter()).unwrap();
+        assert_eq!(tbl2_data, one_batch);
+    }
+
     #[tokio::test]
     async fn drop_table() {
         let tmp_dir = tempdir().unwrap();

rust/lancedb/src/database.rs

@@ -18,8 +18,13 @@ use std::collections::HashMap;
 use std::sync::Arc;
 
 use arrow_array::RecordBatchReader;
+use async_trait::async_trait;
+use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
+use futures::stream;
 use lance::dataset::ReadParams;
+use lance_datafusion::utils::StreamingWriteSource;
 
+use crate::arrow::{SendableRecordBatchStream, SendableRecordBatchStreamExt};
 use crate::error::Result;
 use crate::table::{BaseTable, TableDefinition, WriteOptions};
 
@@ -81,12 +86,41 @@ impl Default for CreateTableMode {
 
 /// The data to start a table or a schema to create an empty table
 pub enum CreateTableData {
-    /// Creates a table using data, no schema required as it will be obtained from the data
+    /// Creates a table using an iterator of data, the schema will be obtained from the data
     Data(Box<dyn RecordBatchReader + Send>),
+    /// Creates a table using a stream of data, the schema will be obtained from the data
+    StreamingData(SendableRecordBatchStream),
     /// Creates an empty table, the definition / schema must be provided separately
     Empty(TableDefinition),
 }
 
+impl CreateTableData {
+    pub fn schema(&self) -> Arc<arrow_schema::Schema> {
+        match self {
+            Self::Data(reader) => reader.schema(),
+            Self::StreamingData(stream) => stream.schema(),
+            Self::Empty(definition) => definition.schema.clone(),
+        }
+    }
+}
+
+#[async_trait]
+impl StreamingWriteSource for CreateTableData {
+    fn arrow_schema(&self) -> Arc<arrow_schema::Schema> {
+        self.schema()
+    }
+    fn into_stream(self) -> datafusion_physical_plan::SendableRecordBatchStream {
+        match self {
+            Self::Data(reader) => reader.into_stream(),
+            Self::StreamingData(stream) => stream.into_df_stream(),
+            Self::Empty(table_definition) => {
+                let schema = table_definition.schema.clone();
+                Box::pin(RecordBatchStreamAdapter::new(schema, stream::empty()))
+            }
+        }
+    }
+}
+
 /// A request to create a table
 pub struct CreateTableRequest {
     /// The name of the new table

rust/lancedb/src/database/listing.rs

@@ -7,9 +7,9 @@ use std::fs::create_dir_all;
 use std::path::Path;
 use std::{collections::HashMap, sync::Arc};
 
-use arrow_array::RecordBatchIterator;
 use lance::dataset::{ReadParams, WriteMode};
 use lance::io::{ObjectStore, ObjectStoreParams, ObjectStoreRegistry, WrappingObjectStore};
+use lance_datafusion::utils::StreamingWriteSource;
 use lance_encoding::version::LanceFileVersion;
 use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
@@ -22,8 +22,8 @@ use crate::table::NativeTable;
 use crate::utils::validate_table_name;
 
 use super::{
-    BaseTable, CreateTableData, CreateTableMode, CreateTableRequest, Database, DatabaseOptions,
-    OpenTableRequest, TableNamesRequest,
+    BaseTable, CreateTableMode, CreateTableRequest, Database, DatabaseOptions, OpenTableRequest,
+    TableNamesRequest,
 };
 
 /// File extension to indicate a lance table
@@ -322,6 +322,37 @@ impl ListingDatabase {
 
         Ok(uri)
     }
+
+    async fn drop_tables(&self, names: Vec<String>) -> Result<()> {
+        let object_store_params = ObjectStoreParams {
+            storage_options: Some(self.storage_options.clone()),
+            ..Default::default()
+        };
+        let mut uri = self.uri.clone();
+        if let Some(query_string) = &self.query_string {
+            uri.push_str(&format!("?{}", query_string));
+        }
+        let commit_handler = commit_handler_from_url(&uri, &Some(object_store_params)).await?;
+        for name in names {
+            let dir_name = format!("{}.{}", name, LANCE_EXTENSION);
+            let full_path = self.base_path.child(dir_name.clone());
+
+            commit_handler.delete(&full_path).await?;
+
+            self.object_store
+                .remove_dir_all(full_path.clone())
+                .await
+                .map_err(|err| match err {
+                    // this error is not lance::Error::DatasetNotFound, as the method
+                    // `remove_dir_all` may be used to remove something not be a dataset
+                    lance::Error::NotFound { .. } => Error::TableNotFound {
+                        name: name.to_owned(),
+                    },
+                    _ => Error::from(err),
+                })?;
+        }
+        Ok(())
+    }
 }
 
 #[async_trait::async_trait]
@@ -401,19 +432,12 @@ impl Database for ListingDatabase {
             write_params.mode = WriteMode::Overwrite;
         }
 
-        let data = match request.data {
-            CreateTableData::Data(data) => data,
-            CreateTableData::Empty(table_definition) => {
-                let schema = table_definition.schema.clone();
-                Box::new(RecordBatchIterator::new(vec![], schema))
-            }
-        };
-        let data_schema = data.schema();
+        let data_schema = request.data.arrow_schema();
 
         match NativeTable::create(
             &table_uri,
             &request.name,
-            data,
+            request.data,
             self.store_wrapper.clone(),
             Some(write_params),
             self.read_consistency_interval,
@@ -500,40 +524,12 @@ impl Database for ListingDatabase {
     }
 
     async fn drop_table(&self, name: &str) -> Result<()> {
-        let dir_name = format!("{}.{}", name, LANCE_EXTENSION);
-        let full_path = self.base_path.child(dir_name.clone());
-        self.object_store
-            .remove_dir_all(full_path.clone())
-            .await
-            .map_err(|err| match err {
-                // this error is not lance::Error::DatasetNotFound,
-                // as the method `remove_dir_all` may be used to remove something not be a dataset
-                lance::Error::NotFound { .. } => Error::TableNotFound {
-                    name: name.to_owned(),
-                },
-                _ => Error::from(err),
-            })?;
-
-        let object_store_params = ObjectStoreParams {
-            storage_options: Some(self.storage_options.clone()),
-            ..Default::default()
-        };
-        let mut uri = self.uri.clone();
-        if let Some(query_string) = &self.query_string {
-            uri.push_str(&format!("?{}", query_string));
-        }
-        let commit_handler = commit_handler_from_url(&uri, &Some(object_store_params))
-            .await
-            .unwrap();
-        commit_handler.delete(&full_path).await.unwrap();
-        Ok(())
+        self.drop_tables(vec![name.to_string()]).await
     }
 
     async fn drop_all_tables(&self) -> Result<()> {
-        self.object_store
-            .remove_dir_all(self.base_path.clone())
-            .await?;
-        Ok(())
+        let tables = self.table_names(TableNamesRequest::default()).await?;
+        self.drop_tables(tables).await
     }
 
     fn as_any(&self) -> &dyn std::any::Any {

rust/lancedb/src/error.rs

@@ -15,6 +15,10 @@ pub enum Error {
     InvalidInput { message: String },
     #[snafu(display("Table '{name}' was not found"))]
     TableNotFound { name: String },
+    #[snafu(display("Database '{name}' was not found"))]
+    DatabaseNotFound { name: String },
+    #[snafu(display("Database '{name}' already exists."))]
+    DatabaseAlreadyExists { name: String },
     #[snafu(display("Index '{name}' was not found"))]
     IndexNotFound { name: String },
     #[snafu(display("Embedding function '{name}' was not found. : {reason}"))]

rust/lancedb/src/lib.rs

@@ -191,6 +191,7 @@
 //! ```
 
 pub mod arrow;
+pub mod catalog;
 pub mod connection;
 pub mod data;
 pub mod database;

rust/lancedb/src/query.rs

@@ -470,6 +470,9 @@ impl<T: HasQuery> QueryBase for T {
     }
 
     fn full_text_search(mut self, query: FullTextSearchQuery) -> Self {
+        if self.mut_query().limit.is_none() {
+            self.mut_query().limit = Some(DEFAULT_TOP_K);
+        }
         self.mut_query().full_text_search = Some(query);
         self
     }
@@ -634,7 +637,7 @@ pub struct QueryRequest {
 impl Default for QueryRequest {
     fn default() -> Self {
         Self {
-            limit: Some(DEFAULT_TOP_K),
+            limit: None,
             offset: None,
             filter: None,
             full_text_search: None,
@@ -719,6 +722,11 @@ impl Query {
         let mut vector_query = self.into_vector();
         let query_vector = vector.to_query_vector(&DataType::Float32, "default")?;
         vector_query.request.query_vector.push(query_vector);
+
+        if vector_query.request.base.limit.is_none() {
+            vector_query.request.base.limit = Some(DEFAULT_TOP_K);
+        }
+
         Ok(vector_query)
     }
 

rust/lancedb/src/remote/db.rs

@@ -19,12 +19,41 @@ use crate::database::{
 };
 use crate::error::Result;
 use crate::table::BaseTable;
+use crate::Error;
 
 use super::client::{ClientConfig, HttpSend, RequestResultExt, RestfulLanceDbClient, Sender};
 use super::table::RemoteTable;
-use super::util::batches_to_ipc_bytes;
+use super::util::{batches_to_ipc_bytes, parse_server_version};
 use super::ARROW_STREAM_CONTENT_TYPE;
 
+// the versions of the server that we support
+// for any new feature that we need to change the SDK behavior, we should bump the server version,
+// and add a feature flag as method of `ServerVersion` here.
+pub const DEFAULT_SERVER_VERSION: semver::Version = semver::Version::new(0, 1, 0);
+#[derive(Debug, Clone)]
+pub struct ServerVersion(pub semver::Version);
+
+impl Default for ServerVersion {
+    fn default() -> Self {
+        Self(DEFAULT_SERVER_VERSION.clone())
+    }
+}
+
+impl ServerVersion {
+    pub fn parse(version: &str) -> Result<Self> {
+        let version = Self(
+            semver::Version::parse(version).map_err(|e| Error::InvalidInput {
+                message: e.to_string(),
+            })?,
+        );
+        Ok(version)
+    }
+
+    pub fn support_multivector(&self) -> bool {
+        self.0 >= semver::Version::new(0, 2, 0)
+    }
+}
+
 #[derive(Deserialize)]
 struct ListTablesResponse {
     tables: Vec<String>,
@@ -33,7 +62,7 @@ struct ListTablesResponse {
 #[derive(Debug)]
 pub struct RemoteDatabase<S: HttpSend = Sender> {
     client: RestfulLanceDbClient<S>,
-    table_cache: Cache<String, ()>,
+    table_cache: Cache<String, Arc<RemoteTable<S>>>,
 }
 
 impl RemoteDatabase {
@@ -115,13 +144,19 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
         }
         let (request_id, rsp) = self.client.send(req, true).await?;
         let rsp = self.client.check_response(&request_id, rsp).await?;
+        let version = parse_server_version(&request_id, &rsp)?;
         let tables = rsp
             .json::<ListTablesResponse>()
             .await
             .err_to_http(request_id)?
             .tables;
         for table in &tables {
-            self.table_cache.insert(table.clone(), ()).await;
+            let remote_table = Arc::new(RemoteTable::new(
+                self.client.clone(),
+                table.clone(),
+                version.clone(),
+            ));
+            self.table_cache.insert(table.clone(), remote_table).await;
         }
         Ok(tables)
     }
@@ -129,6 +164,11 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
     async fn create_table(&self, request: CreateTableRequest) -> Result<Arc<dyn BaseTable>> {
         let data = match request.data {
             CreateTableData::Data(data) => data,
+            CreateTableData::StreamingData(_) => {
+                return Err(Error::NotSupported {
+                    message: "Creating a remote table from a streaming source".to_string(),
+                })
+            }
             CreateTableData::Empty(table_definition) => {
                 let schema = table_definition.schema.clone();
                 Box::new(RecordBatchIterator::new(vec![], schema))
@@ -187,34 +227,42 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
                 return Err(crate::Error::InvalidInput { message: body });
             }
         }
-
-        self.client.check_response(&request_id, rsp).await?;
-
-        self.table_cache.insert(request.name.clone(), ()).await;
-
-        Ok(Arc::new(RemoteTable::new(
+        let rsp = self.client.check_response(&request_id, rsp).await?;
+        let version = parse_server_version(&request_id, &rsp)?;
+        let table = Arc::new(RemoteTable::new(
             self.client.clone(),
-            request.name,
-        )))
+            request.name.clone(),
+            version,
+        ));
+        self.table_cache
+            .insert(request.name.clone(), table.clone())
+            .await;
+
+        Ok(table)
     }
 
     async fn open_table(&self, request: OpenTableRequest) -> Result<Arc<dyn BaseTable>> {
         // We describe the table to confirm it exists before moving on.
-        if self.table_cache.get(&request.name).await.is_none() {
+        if let Some(table) = self.table_cache.get(&request.name).await {
+            Ok(table.clone())
+        } else {
             let req = self
                 .client
                 .post(&format!("/v1/table/{}/describe/", request.name));
-            let (request_id, resp) = self.client.send(req, true).await?;
-            if resp.status() == StatusCode::NOT_FOUND {
+            let (request_id, rsp) = self.client.send(req, true).await?;
+            if rsp.status() == StatusCode::NOT_FOUND {
                 return Err(crate::Error::TableNotFound { name: request.name });
             }
-            self.client.check_response(&request_id, resp).await?;
-        }
-
-        Ok(Arc::new(RemoteTable::new(
+            let rsp = self.client.check_response(&request_id, rsp).await?;
+            let version = parse_server_version(&request_id, &rsp)?;
+            let table = Arc::new(RemoteTable::new(
                 self.client.clone(),
-            request.name,
-        )))
+                request.name.clone(),
+                version,
+            ));
+            self.table_cache.insert(request.name, table.clone()).await;
+            Ok(table)
+        }
     }
 
     async fn rename_table(&self, current_name: &str, new_name: &str) -> Result<()> {
@@ -224,8 +272,10 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
         let req = req.json(&serde_json::json!({ "new_table_name": new_name }));
         let (request_id, resp) = self.client.send(req, false).await?;
         self.client.check_response(&request_id, resp).await?;
-        self.table_cache.remove(current_name).await;
-        self.table_cache.insert(new_name.into(), ()).await;
+        let table = self.table_cache.remove(current_name).await;
+        if let Some(table) = table {
+            self.table_cache.insert(new_name.into(), table).await;
+        }
         Ok(())
     }
 

rust/lancedb/src/remote/table.rs

@@ -10,7 +10,7 @@ use crate::index::IndexStatistics;
 use crate::query::{QueryFilter, QueryRequest, Select, VectorQueryRequest};
 use crate::table::{AddDataMode, AnyQuery, Filter};
 use crate::utils::{supported_btree_data_type, supported_vector_data_type};
-use crate::{DistanceType, Error};
+use crate::{DistanceType, Error, Table};
 use arrow_array::RecordBatchReader;
 use arrow_ipc::reader::FileReader;
 use arrow_schema::{DataType, SchemaRef};
@@ -24,7 +24,7 @@ use http::StatusCode;
 use lance::arrow::json::{JsonDataType, JsonSchema};
 use lance::dataset::scanner::DatasetRecordBatchStream;
 use lance::dataset::{ColumnAlteration, NewColumnTransform, Version};
-use lance_datafusion::exec::OneShotExec;
+use lance_datafusion::exec::{execute_plan, OneShotExec};
 use serde::{Deserialize, Serialize};
 use tokio::sync::RwLock;
 
@@ -41,6 +41,7 @@ use crate::{
 
 use super::client::RequestResultExt;
 use super::client::{HttpSend, RestfulLanceDbClient, Sender};
+use super::db::ServerVersion;
 use super::ARROW_STREAM_CONTENT_TYPE;
 
 #[derive(Debug)]
@@ -48,15 +49,21 @@ pub struct RemoteTable<S: HttpSend = Sender> {
     #[allow(dead_code)]
     client: RestfulLanceDbClient<S>,
     name: String,
+    server_version: ServerVersion,
 
     version: RwLock<Option<u64>>,
 }
 
 impl<S: HttpSend> RemoteTable<S> {
-    pub fn new(client: RestfulLanceDbClient<S>, name: String) -> Self {
+    pub fn new(
+        client: RestfulLanceDbClient<S>,
+        name: String,
+        server_version: ServerVersion,
+    ) -> Self {
         Self {
             client,
             name,
+            server_version,
             version: RwLock::new(None),
         }
     }
@@ -154,9 +161,9 @@ impl<S: HttpSend> RemoteTable<S> {
             body["offset"] = serde_json::Value::Number(serde_json::Number::from(offset));
         }
 
-        if let Some(limit) = params.limit {
+        // Server requires k.
+        let limit = params.limit.unwrap_or(usize::MAX);
         body["k"] = serde_json::Value::Number(serde_json::Number::from(limit));
-        }
 
         if let Some(filter) = &params.filter {
             if let QueryFilter::Sql(filter) = filter {
@@ -212,10 +219,11 @@ impl<S: HttpSend> RemoteTable<S> {
     }
 
     fn apply_vector_query_params(
-        body: &mut serde_json::Value,
+        &self,
+        mut body: serde_json::Value,
         query: &VectorQueryRequest,
-    ) -> Result<()> {
-        Self::apply_query_params(body, &query.base)?;
+    ) -> Result<Vec<serde_json::Value>> {
+        Self::apply_query_params(&mut body, &query.base)?;
 
         // Apply general parameters, before we dispatch based on number of query vectors.
         body["distance_type"] = serde_json::json!(query.distance_type.unwrap_or_default());
@@ -256,25 +264,40 @@ impl<S: HttpSend> RemoteTable<S> {
             }
         }
 
-        match query.query_vector.len() {
+        let bodies = match query.query_vector.len() {
             0 => {
                 // Server takes empty vector, not null or undefined.
                 body["vector"] = serde_json::Value::Array(Vec::new());
+                vec![body]
             }
             1 => {
                 body["vector"] = vector_to_json(&query.query_vector[0])?;
+                vec![body]
             }
             _ => {
+                if self.server_version.support_multivector() {
                     let vectors = query
                         .query_vector
                         .iter()
                         .map(vector_to_json)
                         .collect::<Result<Vec<_>>>()?;
                     body["vector"] = serde_json::Value::Array(vectors);
+                    vec![body]
+                } else {
+                    // Server does not support multiple vectors in a single query.
+                    // We need to send multiple requests.
+                    let mut bodies = Vec::with_capacity(query.query_vector.len());
+                    for vector in &query.query_vector {
+                        let mut body = body.clone();
+                        body["vector"] = vector_to_json(vector)?;
+                        bodies.push(body);
+                    }
+                    bodies
                 }
             }
+        };
 
-        Ok(())
+        Ok(bodies)
     }
 
     async fn check_mutable(&self) -> Result<()> {
@@ -299,27 +322,34 @@ impl<S: HttpSend> RemoteTable<S> {
         &self,
         query: &AnyQuery,
         _options: QueryExecutionOptions,
-    ) -> Result<Pin<Box<dyn RecordBatchStream + Send>>> {
+    ) -> Result<Vec<Pin<Box<dyn RecordBatchStream + Send>>>> {
         let request = self.client.post(&format!("/v1/table/{}/query/", self.name));
 
         let version = self.current_version().await;
         let mut body = serde_json::json!({ "version": version });
 
-        match query {
+        let requests = match query {
             AnyQuery::Query(query) => {
                 Self::apply_query_params(&mut body, query)?;
                 // Empty vector can be passed if no vector search is performed.
                 body["vector"] = serde_json::Value::Array(Vec::new());
+                vec![request.json(&body)]
             }
             AnyQuery::VectorQuery(query) => {
-                Self::apply_vector_query_params(&mut body, query)?;
-            }
+                let bodies = self.apply_vector_query_params(body, query)?;
+                bodies
+                    .into_iter()
+                    .map(|body| request.try_clone().unwrap().json(&body))
+                    .collect()
             }
+        };
 
-        let request = request.json(&body);
-        let (request_id, response) = self.client.send(request, true).await?;
-        let stream = self.read_arrow_stream(&request_id, response).await?;
-        Ok(stream)
+        let futures = requests.into_iter().map(|req| async move {
+            let (request_id, response) = self.client.send(req, true).await?;
+            self.read_arrow_stream(&request_id, response).await
+        });
+        let streams = futures::future::try_join_all(futures).await?;
+        Ok(streams)
     }
 }
 
@@ -342,7 +372,7 @@ mod test_utils {
     use crate::remote::client::test_utils::MockSender;
 
     impl RemoteTable<MockSender> {
-        pub fn new_mock<F, T>(name: String, handler: F) -> Self
+        pub fn new_mock<F, T>(name: String, handler: F, version: Option<semver::Version>) -> Self
         where
             F: Fn(reqwest::Request) -> http::Response<T> + Send + Sync + 'static,
             T: Into<reqwest::Body>,
@@ -351,6 +381,7 @@ mod test_utils {
             Self {
                 client,
                 name,
+                server_version: version.map(ServerVersion).unwrap_or_default(),
                 version: RwLock::new(None),
             }
         }
@@ -491,8 +522,17 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
         query: &AnyQuery,
         options: QueryExecutionOptions,
     ) -> Result<Arc<dyn ExecutionPlan>> {
-        let stream = self.execute_query(query, options).await?;
+        let streams = self.execute_query(query, options).await?;
+        if streams.len() == 1 {
+            let stream = streams.into_iter().next().unwrap();
             Ok(Arc::new(OneShotExec::new(stream)))
+        } else {
+            let stream_execs = streams
+                .into_iter()
+                .map(|stream| Arc::new(OneShotExec::new(stream)) as Arc<dyn ExecutionPlan>)
+                .collect();
+            Table::multi_vector_plan(stream_execs)
+        }
     }
 
     async fn query(
@@ -500,8 +540,24 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
         query: &AnyQuery,
         _options: QueryExecutionOptions,
     ) -> Result<DatasetRecordBatchStream> {
-        let stream = self.execute_query(query, _options).await?;
-        Ok(DatasetRecordBatchStream::new(stream))
+        let streams = self.execute_query(query, _options).await?;
+
+        if streams.len() == 1 {
+            Ok(DatasetRecordBatchStream::new(
+                streams.into_iter().next().unwrap(),
+            ))
+        } else {
+            let stream_execs = streams
+                .into_iter()
+                .map(|stream| Arc::new(OneShotExec::new(stream)) as Arc<dyn ExecutionPlan>)
+                .collect();
+            let plan = Table::multi_vector_plan(stream_execs)?;
+
+            Ok(DatasetRecordBatchStream::new(execute_plan(
+                plan,
+                Default::default(),
+            )?))
+        }
     }
     async fn update(&self, update: UpdateBuilder) -> Result<u64> {
         self.check_mutable().await?;
@@ -884,8 +940,10 @@ mod tests {
     use futures::{future::BoxFuture, StreamExt, TryFutureExt};
     use lance_index::scalar::FullTextSearchQuery;
     use reqwest::Body;
+    use rstest::rstest;
 
     use crate::index::vector::IvfFlatIndexBuilder;
+    use crate::remote::db::DEFAULT_SERVER_VERSION;
     use crate::remote::JSON_CONTENT_TYPE;
     use crate::{
         index::{vector::IvfPqIndexBuilder, Index, IndexStatistics, IndexType},
@@ -1293,6 +1351,52 @@ mod tests {
         table.delete("id in (1, 2, 3)").await.unwrap();
     }
 
+    #[tokio::test]
+    async fn test_query_plain() {
+        let expected_data = RecordBatch::try_new(
+            Arc::new(Schema::new(vec![Field::new("a", DataType::Int32, false)])),
+            vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
+        )
+        .unwrap();
+        let expected_data_ref = expected_data.clone();
+
+        let table = Table::new_with_handler("my_table", move |request| {
+            assert_eq!(request.method(), "POST");
+            assert_eq!(request.url().path(), "/v1/table/my_table/query/");
+            assert_eq!(
+                request.headers().get("Content-Type").unwrap(),
+                JSON_CONTENT_TYPE
+            );
+
+            let body = request.body().unwrap().as_bytes().unwrap();
+            let body: serde_json::Value = serde_json::from_slice(body).unwrap();
+            let expected_body = serde_json::json!({
+                "k": usize::MAX,
+                "prefilter": true,
+                "vector": [], // Empty vector means no vector query.
+                "version": null,
+            });
+            assert_eq!(body, expected_body);
+
+            let response_body = write_ipc_file(&expected_data_ref);
+            http::Response::builder()
+                .status(200)
+                .header(CONTENT_TYPE, ARROW_FILE_CONTENT_TYPE)
+                .body(response_body)
+                .unwrap()
+        });
+
+        let data = table
+            .query()
+            .execute()
+            .await
+            .unwrap()
+            .collect::<Vec<_>>()
+            .await;
+        assert_eq!(data.len(), 1);
+        assert_eq!(data[0].as_ref().unwrap(), &expected_data);
+    }
+
     #[tokio::test]
     async fn test_query_vector_default_values() {
         let expected_data = RecordBatch::try_new(
@@ -1508,9 +1612,12 @@ mod tests {
             .unwrap();
     }
 
+    #[rstest]
+    #[case(DEFAULT_SERVER_VERSION.clone())]
+    #[case(semver::Version::new(0, 2, 0))]
     #[tokio::test]
-    async fn test_query_multiple_vectors() {
-        let table = Table::new_with_handler("my_table", |request| {
+    async fn test_batch_queries(#[case] version: semver::Version) {
+        let table = Table::new_with_handler_version("my_table", version.clone(), move |request| {
             assert_eq!(request.method(), "POST");
             assert_eq!(request.url().path(), "/v1/table/my_table/query/");
             assert_eq!(
@@ -1520,10 +1627,12 @@ mod tests {
             let body: serde_json::Value =
                 serde_json::from_slice(request.body().unwrap().as_bytes().unwrap()).unwrap();
             let query_vectors = body["vector"].as_array().unwrap();
+            let version = ServerVersion(version.clone());
+            let data = if version.support_multivector() {
                 assert_eq!(query_vectors.len(), 2);
                 assert_eq!(query_vectors[0].as_array().unwrap().len(), 3);
                 assert_eq!(query_vectors[1].as_array().unwrap().len(), 3);
-            let data = RecordBatch::try_new(
+                RecordBatch::try_new(
                     Arc::new(Schema::new(vec![
                         Field::new("a", DataType::Int32, false),
                         Field::new("query_index", DataType::Int32, false),
@@ -1533,7 +1642,17 @@ mod tests {
                         Arc::new(Int32Array::from(vec![0, 0, 0, 1, 1, 1])),
                     ],
                 )
-            .unwrap();
+                .unwrap()
+            } else {
+                // it's single flat vector, so here the length is dim
+                assert_eq!(query_vectors.len(), 3);
+                RecordBatch::try_new(
+                    Arc::new(Schema::new(vec![Field::new("a", DataType::Int32, false)])),
+                    vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
+                )
+                .unwrap()
+            };
+
             let response_body = write_ipc_file(&data);
             http::Response::builder()
                 .status(200)

rust/lancedb/src/remote/util.rs

@@ -4,9 +4,12 @@
 use std::io::Cursor;
 
 use arrow_array::RecordBatchReader;
+use reqwest::Response;
 
 use crate::Result;
 
+use super::db::ServerVersion;
+
 pub fn batches_to_ipc_bytes(batches: impl RecordBatchReader) -> Result<Vec<u8>> {
     const WRITE_BUF_SIZE: usize = 4096;
     let buf = Vec::with_capacity(WRITE_BUF_SIZE);
@@ -22,3 +25,24 @@ pub fn batches_to_ipc_bytes(batches: impl RecordBatchReader) -> Result<Vec<u8>>
     }
     Ok(buf.into_inner())
 }
+
+pub fn parse_server_version(req_id: &str, rsp: &Response) -> Result<ServerVersion> {
+    let version = rsp
+        .headers()
+        .get("phalanx-version")
+        .map(|v| {
+            let v = v.to_str().map_err(|e| crate::Error::Http {
+                source: e.into(),
+                request_id: req_id.to_string(),
+                status_code: Some(rsp.status()),
+            })?;
+            ServerVersion::parse(v).map_err(|e| crate::Error::Http {
+                source: e.into(),
+                request_id: req_id.to_string(),
+                status_code: Some(rsp.status()),
+            })
+        })
+        .transpose()?
+        .unwrap_or_default();
+    Ok(version)
+}

rust/lancedb/src/table.rs

@@ -28,13 +28,13 @@ pub use lance::dataset::NewColumnTransform;
 pub use lance::dataset::ReadParams;
 pub use lance::dataset::Version;
 use lance::dataset::{
-    Dataset, InsertBuilder, UpdateBuilder as LanceUpdateBuilder, WhenMatched, WriteMode,
-    WriteParams,
+    InsertBuilder, UpdateBuilder as LanceUpdateBuilder, WhenMatched, WriteMode, WriteParams,
 };
 use lance::dataset::{MergeInsertBuilder as LanceMergeInsertBuilder, WhenNotMatchedBySource};
 use lance::index::vector::utils::infer_vector_dim;
 use lance::io::WrappingObjectStore;
 use lance_datafusion::exec::execute_plan;
+use lance_datafusion::utils::StreamingWriteSource;
 use lance_index::vector::hnsw::builder::HnswBuildParams;
 use lance_index::vector::ivf::IvfBuildParams;
 use lance_index::vector::pq::PQBuildParams;
@@ -509,6 +509,27 @@ mod test_utils {
             let inner = Arc::new(crate::remote::table::RemoteTable::new_mock(
                 name.into(),
                 handler,
+                None,
+            ));
+            Self {
+                inner,
+                // Registry is unused.
+                embedding_registry: Arc::new(MemoryRegistry::new()),
+            }
+        }
+
+        pub fn new_with_handler_version<T>(
+            name: impl Into<String>,
+            version: semver::Version,
+            handler: impl Fn(reqwest::Request) -> http::Response<T> + Clone + Send + Sync + 'static,
+        ) -> Self
+        where
+            T: Into<reqwest::Body>,
+        {
+            let inner = Arc::new(crate::remote::table::RemoteTable::new_mock(
+                name.into(),
+                handler,
+                Some(version),
             ));
             Self {
                 inner,
@@ -1243,7 +1264,7 @@ impl NativeTable {
     pub async fn create(
         uri: &str,
         name: &str,
-        batches: impl RecordBatchReader + Send + 'static,
+        batches: impl StreamingWriteSource,
         write_store_wrapper: Option<Arc<dyn WrappingObjectStore>>,
         params: Option<WriteParams>,
         read_consistency_interval: Option<std::time::Duration>,
@@ -1258,7 +1279,9 @@ impl NativeTable {
             None => params,
         };
 
-        let dataset = Dataset::write(batches, uri, Some(params))
+        let insert_builder = InsertBuilder::new(uri).with_params(&params);
+        let dataset = insert_builder
+            .execute_stream(batches)
             .await
             .map_err(|e| match e {
                 lance::Error::DatasetAlreadyExists { .. } => Error::TableAlreadyExists {
@@ -1266,6 +1289,7 @@ impl NativeTable {
                 },
                 source => Error::Lance { source },
             })?;
+
         Ok(Self {
             name: name.to_string(),
             uri: uri.to_string(),
@@ -2370,8 +2394,9 @@ mod tests {
     use arrow_data::ArrayDataBuilder;
     use arrow_schema::{DataType, Field, Schema, TimeUnit};
     use futures::TryStreamExt;
-    use lance::dataset::{Dataset, WriteMode};
+    use lance::dataset::WriteMode;
     use lance::io::{ObjectStoreParams, WrappingObjectStore};
+    use lance::Dataset;
     use rand::Rng;
     use tempfile::tempdir;
 
@@ -2421,6 +2446,7 @@ mod tests {
         let uri = tmp_dir.path().to_str().unwrap();
 
         let batches = make_test_batches();
+        let batches = Box::new(batches) as Box<dyn RecordBatchReader + Send>;
         let table = NativeTable::create(uri, "test", batches, None, None, None)
             .await
             .unwrap();

rust/lancedb/src/table/datafusion.rs

@@ -4,6 +4,7 @@
 //! This module contains adapters to allow LanceDB tables to be used as DataFusion table providers.
 use std::{collections::HashMap, sync::Arc};
 
+use arrow_array::RecordBatch;
 use arrow_schema::Schema as ArrowSchema;
 use async_trait::async_trait;
 use datafusion_catalog::{Session, TableProvider};
@@ -104,7 +105,9 @@ impl ExecutionPlan for MetadataEraserExec {
     ) -> DataFusionResult<SendableRecordBatchStream> {
         let stream = self.input.execute(partition, context)?;
         let schema = self.schema.clone();
-        let stream = stream.map_ok(move |batch| batch.with_schema(schema.clone()).unwrap());
+        let stream = stream.map_ok(move |batch| {
+            RecordBatch::try_new(schema.clone(), batch.columns().to_vec()).unwrap()
+        });
         Ok(
             Box::pin(RecordBatchStreamAdapter::new(self.schema.clone(), stream))
                 as SendableRecordBatchStream,
@@ -148,7 +151,7 @@ impl TableProvider for BaseTableAdapter {
 
     async fn scan(
         &self,
-        _state: &dyn Session,
+        state: &dyn Session,
         projection: Option<&Vec<usize>>,
         filters: &[Expr],
         limit: Option<usize>,
@@ -174,9 +177,15 @@ impl TableProvider for BaseTableAdapter {
             // Need to override the default of 10
             query.limit = None;
         }
+
+        let options = QueryExecutionOptions {
+            max_batch_length: state.config().batch_size() as u32,
+            ..Default::default()
+        };
+
         let plan = self
             .table
-            .create_plan(&AnyQuery::Query(query), QueryExecutionOptions::default())
+            .create_plan(&AnyQuery::Query(query), options)
             .map_err(|err| DataFusionError::External(err.into()))
             .await?;
         Ok(Arc::new(MetadataEraserExec::new(plan)))
@@ -201,14 +210,18 @@ pub mod tests {
 
     use arrow::array::AsArray;
     use arrow_array::{
-        Int32Array, RecordBatch, RecordBatchIterator, RecordBatchReader, UInt32Array,
+        BinaryArray, Float64Array, Int32Array, Int64Array, RecordBatch, RecordBatchIterator,
+        RecordBatchReader, StringArray, UInt32Array,
     };
     use arrow_schema::{DataType, Field, Schema};
-    use datafusion::{datasource::provider_as_source, prelude::SessionContext};
+    use datafusion::{
+        datasource::provider_as_source,
+        prelude::{SessionConfig, SessionContext},
+    };
     use datafusion_catalog::TableProvider;
     use datafusion_execution::SendableRecordBatchStream;
     use datafusion_expr::{col, lit, LogicalPlan, LogicalPlanBuilder};
-    use futures::TryStreamExt;
+    use futures::{StreamExt, TryStreamExt};
     use tempfile::tempdir;
 
     use crate::{
@@ -238,9 +251,49 @@ pub mod tests {
         )
     }
 
+    fn make_tbl_two_test_batches() -> impl RecordBatchReader + Send + Sync + 'static {
+        let metadata = HashMap::from_iter(vec![("foo".to_string(), "bar".to_string())]);
+        let schema = Arc::new(
+            Schema::new(vec![
+                Field::new("ints", DataType::Int64, true),
+                Field::new("strings", DataType::Utf8, true),
+                Field::new("floats", DataType::Float64, true),
+                Field::new("jsons", DataType::Utf8, true),
+                Field::new("bins", DataType::Binary, true),
+                Field::new("nodates", DataType::Utf8, true),
+            ])
+            .with_metadata(metadata),
+        );
+        RecordBatchIterator::new(
+            vec![RecordBatch::try_new(
+                schema.clone(),
+                vec![
+                    Arc::new(Int64Array::from_iter_values(0..1000)),
+                    Arc::new(StringArray::from_iter_values(
+                        (0..1000).map(|i| i.to_string()),
+                    )),
+                    Arc::new(Float64Array::from_iter_values((0..1000).map(|i| i as f64))),
+                    Arc::new(StringArray::from_iter_values(
+                        (0..1000).map(|i| format!("{{\"i\":{}}}", i)),
+                    )),
+                    Arc::new(BinaryArray::from_iter_values(
+                        (0..1000).map(|i| (i as u32).to_be_bytes().to_vec()),
+                    )),
+                    Arc::new(StringArray::from_iter_values(
+                        (0..1000).map(|i| i.to_string()),
+                    )),
+                ],
+            )],
+            schema,
+        )
+    }
+
     struct TestFixture {
         _tmp_dir: tempfile::TempDir,
+        // An adapter for a table with make_test_batches batches
         adapter: Arc<BaseTableAdapter>,
+        // an adapter for a table with make_tbl_two_test_batches batches
+        adapter2: Arc<BaseTableAdapter>,
     }
 
     impl TestFixture {
@@ -262,20 +315,40 @@ pub mod tests {
                 .await
                 .unwrap();
 
+            let tbl2 = db
+                .create_table("tbl2", make_tbl_two_test_batches())
+                .execute()
+                .await
+                .unwrap();
+
             let adapter = Arc::new(
                 BaseTableAdapter::try_new(tbl.base_table().clone())
                     .await
                     .unwrap(),
             );
 
+            let adapter2 = Arc::new(
+                BaseTableAdapter::try_new(tbl2.base_table().clone())
+                    .await
+                    .unwrap(),
+            );
+
             Self {
                 _tmp_dir: tmp_dir,
                 adapter,
+                adapter2,
             }
         }
 
         async fn plan_to_stream(plan: LogicalPlan) -> SendableRecordBatchStream {
-            SessionContext::new()
+            Self::plan_to_stream_with_config(plan, SessionConfig::default()).await
+        }
+
+        async fn plan_to_stream_with_config(
+            plan: LogicalPlan,
+            config: SessionConfig,
+        ) -> SendableRecordBatchStream {
+            SessionContext::new_with_config(config)
                 .execute_logical_plan(plan)
                 .await
                 .unwrap()
@@ -309,7 +382,7 @@ pub mod tests {
         }
 
         async fn check_plan(plan: LogicalPlan, expected: &str) {
-            let physical_plan = dbg!(Self::plan_to_explain(plan).await);
+            let physical_plan = Self::plan_to_explain(plan).await;
             let mut lines_checked = 0;
             for (actual_line, expected_line) in physical_plan.lines().zip(expected.lines()) {
                 lines_checked += 1;
@@ -325,6 +398,30 @@ pub mod tests {
         }
     }
 
+    #[tokio::test]
+    async fn test_batch_size() {
+        let fixture = TestFixture::new().await;
+
+        let plan = LogicalPlanBuilder::scan("foo", provider_as_source(fixture.adapter2), None)
+            .unwrap()
+            .build()
+            .unwrap();
+
+        let config = SessionConfig::default().with_batch_size(100);
+
+        let stream = TestFixture::plan_to_stream_with_config(plan.clone(), config).await;
+
+        let batch_count = stream.count().await;
+        assert_eq!(batch_count, 10);
+
+        let config = SessionConfig::default().with_batch_size(250);
+
+        let stream = TestFixture::plan_to_stream_with_config(plan, config).await;
+
+        let batch_count = stream.count().await;
+        assert_eq!(batch_count, 4);
+    }
+
     #[tokio::test]
     async fn test_metadata_erased() {
         let fixture = TestFixture::new().await;
@@ -343,6 +440,27 @@ pub mod tests {
         }
     }
 
+    #[tokio::test]
+    async fn test_metadata_erased_with_filter() {
+        // This is a regression test where the metadata eraser was not properly erasing metadata
+        let fixture = TestFixture::new().await;
+
+        assert!(fixture.adapter.schema().metadata().is_empty());
+
+        let plan = LogicalPlanBuilder::scan("foo", provider_as_source(fixture.adapter2), None)
+            .unwrap()
+            .filter(col("ints").lt(lit(10)))
+            .unwrap()
+            .build()
+            .unwrap();
+
+        let mut stream = TestFixture::plan_to_stream(plan).await;
+
+        while let Some(batch) = stream.try_next().await.unwrap() {
+            assert!(batch.schema().metadata().is_empty());
+        }
+    }
+
     #[tokio::test]
     async fn test_filter_pushdown() {
         let fixture = TestFixture::new().await;