chore(deps): bump snafu from 0.8.9 to 0.9.0

Bumps [snafu](https://github.com/shepmaster/snafu) from 0.8.9 to 0.9.0. - [Changelog](https://github.com/shepmaster/snafu/blob/main/CHANGELOG.md) - [Commits](https://github.com/shepmaster/snafu/compare/0.8.9...0.9.0) --- updated-dependencies: - dependency-name: snafu dependency-version: 0.9.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com>
2026-05-23 15:00:39 +00:00 · 2026-05-20 16:12:28 +00:00
42 changed files with 277 additions and 1720 deletions
--- a/.bumpversion.toml
+++ b/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.30.0-beta.1"
+current_version = "0.29.1-beta.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -37,13 +37,10 @@ Before committing changes, run formatting for every language you touched. At min
  and run targeted tests through `cd python && uv run ...`.
 * TypeScript changes: run the relevant `npm`/`pnpm` lint, format, build, and docs commands in `nodejs`.

-Before creating a PR, the exact value passed to `gh pr create --title` must follow
-Conventional Commits, such as `fix: support nested field paths in native index creation`
-or `feat(python): add dataset multiprocessing support`. Do not use a plain natural
-language summary like `Support nested field paths in native index creation` as the PR
-title. The semantic-release check uses the PR title and body as the merge commit message,
-so a non-conventional PR title will fail CI. After creating a PR, read the remote PR title
-back and fix it immediately if it is not conventional.
+Before creating a PR, make sure the PR title follows Conventional Commits, such as
+`fix: support nested field paths in native index creation` or
+`feat(python): add dataset multiprocessing support`. The semantic-release check uses the
+PR title and body as the merge commit message, so a non-conventional PR title will fail CI.

 ## Coding tips

--- a/Cargo.lock
+++ b/Cargo.lock
@@ -5014,7 +5014,7 @@ dependencies = [

 [[package]]
 name = "lancedb"
-version = "0.30.0-beta.1"
+version = "0.29.1-beta.0"
 dependencies = [
 "ahash",
 "anyhow",
@@ -5084,7 +5084,6 @@ dependencies = [
 "serde",
 "serde_json",
 "serde_with",
- "serial_test",
 "snafu 0.8.9",
 "tempfile",
 "test-log",
@@ -5097,7 +5096,7 @@ dependencies = [

 [[package]]
 name = "lancedb-nodejs"
-version = "0.30.0-beta.1"
+version = "0.29.1-beta.0"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5120,7 +5119,7 @@ dependencies = [

 [[package]]
 name = "lancedb-python"
-version = "0.33.0-beta.1"
+version = "0.32.1-beta.0"
 dependencies = [
 "arrow",
 "async-trait",
@@ -6997,7 +6996,7 @@ version = "0.14.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "343d3bd7056eda839b03204e68deff7d1b13aba7af2b2fd16890697274262ee7"
 dependencies = [
- "heck 0.5.0",
+ "heck 0.4.1",
 "itertools 0.14.0",
 "log",
 "multimap",
@@ -8129,15 +8128,6 @@ dependencies = [
 "winapi-util",
 ]

-[[package]]
-name = "scc"
-version = "2.4.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "46e6f046b7fef48e2660c57ed794263155d713de679057f2d0c169bfc6e756cc"
-dependencies = [
- "sdd",
-]
-
 [[package]]
 name = "schannel"
 version = "0.1.29"
@@ -8204,12 +8194,6 @@ dependencies = [
 "untrusted 0.9.0",
 ]

-[[package]]
-name = "sdd"
-version = "3.0.10"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "490dcfcbfef26be6800d11870ff2df8774fa6e86d047e3e8c8a76b25655e41ca"
-
 [[package]]
 name = "sec1"
 version = "0.3.0"
@@ -8400,32 +8384,6 @@ dependencies = [
 "unsafe-libyaml",
 ]

-[[package]]
-name = "serial_test"
-version = "3.4.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "911bd979bf1070a3f3aa7b691a3b3e9968f339ceeec89e08c280a8a22207a32f"
-dependencies = [
- "futures-executor",
- "futures-util",
- "log",
- "once_cell",
- "parking_lot",
- "scc",
- "serial_test_derive",
-]
-
-[[package]]
-name = "serial_test_derive"
-version = "3.4.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0a7d91949b85b0d2fb687445e448b40d322b6b3e4af6b44a29b21d9a5f33e6d9"
-dependencies = [
- "proc-macro2",
- "quote",
- "syn 2.0.117",
-]
-
 [[package]]
 name = "sha1"
 version = "0.10.6"
@@ -8623,7 +8581,7 @@ version = "0.8.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "c1c97747dbf44bb1ca44a561ece23508e99cb592e862f22222dcf42f51d1e451"
 dependencies = [
- "heck 0.5.0",
+ "heck 0.4.1",
 "proc-macro2",
 "quote",
 "syn 2.0.117",
@@ -8635,7 +8593,7 @@ version = "0.9.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "54254b8531cafa275c5e096f62d48c81435d1015405a91198ddb11e967301d40"
 dependencies = [
- "heck 0.5.0",
+ "heck 0.4.1",
 "proc-macro2",
 "quote",
 "syn 2.0.117",
--- a/ci/check_lance_release.py
+++ b/ci/check_lance_release.py
@@ -112,25 +112,25 @@ def fetch_remote_tags() -> List[TagInfo]:
            "api",
            "-X",
            "GET",
-            f"repos/{LANCE_REPO}/releases",
+            f"repos/{LANCE_REPO}/git/refs/tags",
+            "--paginate",
            "--jq",
-            ".[].tag_name",
-            "-F",
-            "per_page=20",
+            ".[].ref",
        ]
    )
    tags: List[TagInfo] = []
    for line in output.splitlines():
-        tag = line.strip()
-        if not tag.startswith("v"):
+        ref = line.strip()
+        if not ref.startswith("refs/tags/v"):
            continue
+        tag = ref.split("refs/tags/")[-1]
        version = tag.lstrip("v")
        try:
            tags.append(TagInfo(tag=tag, version=version, semver=parse_semver(version)))
        except ValueError:
            continue
    if not tags:
-        raise RuntimeError("No Lance releases could be parsed from GitHub API output")
+        raise RuntimeError("No Lance tags could be parsed from GitHub API output")
    return tags


--- a/docs/src/java/java.md
+++ b/docs/src/java/java.md
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.30.0-beta.1</version>
+    <version>0.29.1-beta.0</version>
 </dependency>
 ```

--- a/docs/src/js/interfaces/ConnectionOptions.md
+++ b/docs/src/js/interfaces/ConnectionOptions.md
@@ -70,20 +70,16 @@ client used by manifest-enabled native connections.
 optional readConsistencyInterval: number;
 ```

-The interval, in seconds, at which to check for updates to the table
-from other processes. If None, then consistency is not checked. For
-performance reasons, this is the default. For strong consistency, set
-this to zero seconds. Then every read will check for updates from other
-processes. As a compromise, you can set this to a non-zero value for
-eventual consistency. If more than that interval has passed since the
-last check, then the table will be checked for updates. Note: this
-consistency only applies to read operations. Write operations are
+(For LanceDB OSS only): The interval, in seconds, at which to check for
+updates to the table from other processes. If None, then consistency is not
+checked. For performance reasons, this is the default. For strong
+consistency, set this to zero seconds. Then every read will check for
+updates from other processes. As a compromise, you can set this to a
+non-zero value for eventual consistency. If more than that interval
+has passed since the last check, then the table will be checked for updates.
+Note: this consistency only applies to read operations. Write operations are
 always consistent.

-Stronger consistency is not free. The smaller the interval, the more
-often each read pays the cost of checking for updates against object
-storage, raising per-read latency and cost.
-
 ***

 ### region?
--- a/java/lancedb-core/pom.xml
+++ b/java/lancedb-core/pom.xml
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.30.0-beta.1</version>
+      <version>0.29.1-beta.0</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

--- a/java/pom.xml
+++ b/java/pom.xml
@@ -6,7 +6,7 @@

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.30.0-beta.1</version>
+    <version>0.29.1-beta.0</version>
    <packaging>pom</packaging>
    <name>${project.artifactId}</name>
    <description>LanceDB Java SDK Parent POM</description>
--- a/nodejs/Cargo.toml
+++ b/nodejs/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.30.0-beta.1"
+version = "0.29.1-beta.0"
 publish = false
 license.workspace = true
 description.workspace = true
--- a/nodejs/test/table.test.ts
+++ b/nodejs/test/table.test.ts
@@ -28,7 +28,6 @@ import {
  List,
  Schema,
  SchemaLike,
-  Struct,
  Type,
  Uint8,
  Utf8,
@@ -781,113 +780,6 @@ describe("When creating an index", () => {
    expect(indices2.length).toBe(0);
  });

-  it("should create and search a nested vector index", async () => {
-    const db = await connect(tmpDir.name);
-    const nestedSchema = new Schema([
-      new Field("id", new Int32(), true),
-      new Field(
-        "image",
-        new Struct([
-          new Field(
-            "embedding",
-            new FixedSizeList(2, new Field("item", new Float32(), true)),
-            true,
-          ),
-        ]),
-        true,
-      ),
-    ]);
-    const nestedTable = await db.createTable(
-      "nested_vector",
-      makeArrowTable(
-        Array.from({ length: 300 }, (_, id) => ({
-          id,
-          image: { embedding: [id, id + 1] },
-        })),
-        { schema: nestedSchema },
-      ),
-    );
-
-    await nestedTable.createIndex("image.embedding", {
-      name: "image_embedding_idx",
-    });
-    const indices = await nestedTable.listIndices();
-    expect(indices).toContainEqual({
-      name: "image_embedding_idx",
-      indexType: "IvfPq",
-      columns: ["image.embedding"],
-    });
-
-    const explicit = await nestedTable
-      .query()
-      .nearestTo([0.0, 1.0])
-      .column("image.embedding")
-      .limit(1)
-      .toArray();
-    const inferred = await nestedTable
-      .query()
-      .nearestTo([0.0, 1.0])
-      .limit(1)
-      .toArray();
-    expect(inferred[0].id).toEqual(explicit[0].id);
-  });
-
-  it("should report multiple nested vector candidates", async () => {
-    const db = await connect(tmpDir.name);
-    const nestedSchema = new Schema([
-      new Field(
-        "image",
-        new Struct([
-          new Field(
-            "embedding",
-            new FixedSizeList(2, new Field("item", new Float32(), true)),
-            true,
-          ),
-        ]),
-        true,
-      ),
-      new Field(
-        "text",
-        new Struct([
-          new Field(
-            "embedding",
-            new FixedSizeList(2, new Field("item", new Float32(), true)),
-            true,
-          ),
-        ]),
-        true,
-      ),
-    ]);
-    const nestedTable = await db.createTable(
-      "multiple_nested_vectors",
-      makeArrowTable(
-        [
-          {
-            image: { embedding: [0.0, 1.0] },
-            text: { embedding: [2.0, 3.0] },
-          },
-        ],
-        { schema: nestedSchema },
-      ),
-    );
-
-    await expect(
-      nestedTable.query().nearestTo([0.0, 1.0]).limit(1).toArray(),
-    ).rejects.toThrow(/image\.embedding.*text\.embedding/);
-  });
-
-  it("should report when no default vector column exists", async () => {
-    const db = await connect(tmpDir.name);
-    const noVectorTable = await db.createTable(
-      "no_vector",
-      makeArrowTable([{ id: 0, label: "cat" }]),
-    );
-
-    await expect(
-      noVectorTable.query().nearestTo([0.0, 1.0]).limit(1).toArray(),
-    ).rejects.toThrow(/No vector column/);
-  });
-
  it("should wait for index readiness", async () => {
    // Create an index and then wait for it to be ready
    await tbl.createIndex("vec");
--- a/nodejs/npm/darwin-arm64/package.json
+++ b/nodejs/npm/darwin-arm64/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
--- a/nodejs/npm/linux-arm64-gnu/package.json
+++ b/nodejs/npm/linux-arm64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
--- a/nodejs/npm/linux-arm64-musl/package.json
+++ b/nodejs/npm/linux-arm64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
--- a/nodejs/npm/linux-x64-gnu/package.json
+++ b/nodejs/npm/linux-x64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
--- a/nodejs/npm/linux-x64-musl/package.json
+++ b/nodejs/npm/linux-x64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
--- a/nodejs/npm/win32-arm64-msvc/package.json
+++ b/nodejs/npm/win32-arm64-msvc/package.json
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.30.0-beta.1",
+  "version": "0.29.1-beta.0",
  "os": [
    "win32"
  ],
--- a/nodejs/npm/win32-x64-msvc/package.json
+++ b/nodejs/npm/win32-x64-msvc/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.30.0-beta.1",
+	"version": "0.29.1-beta.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
--- a/nodejs/package-lock.json
+++ b/nodejs/package-lock.json
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.30.0-beta.1",
+  "version": "0.29.1-beta.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.30.0-beta.1",
+      "version": "0.29.1-beta.0",
      "cpu": [
        "x64",
        "arm64"
--- a/nodejs/package.json
+++ b/nodejs/package.json
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.30.0-beta.1",
+  "version": "0.29.1-beta.0",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
--- a/nodejs/src/lib.rs
+++ b/nodejs/src/lib.rs
@@ -24,19 +24,15 @@ mod util;
 #[napi(object)]
 #[derive(Debug)]
 pub struct ConnectionOptions {
-    /// The interval, in seconds, at which to check for updates to the table
-    /// from other processes. If None, then consistency is not checked. For
-    /// performance reasons, this is the default. For strong consistency, set
-    /// this to zero seconds. Then every read will check for updates from other
-    /// processes. As a compromise, you can set this to a non-zero value for
-    /// eventual consistency. If more than that interval has passed since the
-    /// last check, then the table will be checked for updates. Note: this
-    /// consistency only applies to read operations. Write operations are
+    /// (For LanceDB OSS only): The interval, in seconds, at which to check for
+    /// updates to the table from other processes. If None, then consistency is not
+    /// checked. For performance reasons, this is the default. For strong
+    /// consistency, set this to zero seconds. Then every read will check for
+    /// updates from other processes. As a compromise, you can set this to a
+    /// non-zero value for eventual consistency. If more than that interval
+    /// has passed since the last check, then the table will be checked for updates.
+    /// Note: this consistency only applies to read operations. Write operations are
    /// always consistent.
-    ///
-    /// Stronger consistency is not free. The smaller the interval, the more
-    /// often each read pays the cost of checking for updates against object
-    /// storage, raising per-read latency and cost.
    pub read_consistency_interval: Option<f64>,
    /// (For LanceDB OSS only): configuration for object storage.
    ///
--- a/python/.bumpversion.toml
+++ b/python/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.33.0-beta.1"
+current_version = "0.32.1-beta.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/python/Cargo.toml
+++ b/python/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.33.0-beta.1"
+version = "0.32.1-beta.0"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
--- a/python/python/lancedb/init.py
+++ b/python/python/lancedb/init.py
@@ -94,6 +94,7 @@ def connect(
    host_override: str, optional
        The override url for LanceDB Cloud.
    read_consistency_interval: timedelta, default None
+        (For LanceDB OSS only)
        The interval at which to check for updates to the table from other
        processes. If None, then consistency is not checked. For performance
        reasons, this is the default. For strong consistency, set this to
@@ -103,10 +104,6 @@ def connect(
        the last check, then the table will be checked for updates. Note: this
        consistency only applies to read operations. Write operations are
        always consistent.
-
-        Stronger consistency is not free. The smaller the interval, the more
-        often each read pays the cost of checking for updates against object
-        storage, raising per-read latency and cost.
    client_config: ClientConfig or dict, optional
        Configuration options for the LanceDB Cloud HTTP client. If a dict, then
        the keys are the attributes of the ClientConfig class. If None, then the
@@ -150,13 +147,6 @@ def connect(
    >>> db = lancedb.connect("s3://my-bucket/lancedb",
    ...                      storage_options={"aws_access_key_id": "***"})

-    For tests and temporary data, use an in-memory database:
-
-    >>> db = lancedb.connect("memory://")
-
-    In-memory databases are not persisted. Tables are dropped when the last
-    connection or table handle referencing them is closed.
-
    Connect to LanceDB cloud:

    >>> db = lancedb.connect("db://my_database", api_key="ldb_...",
@@ -220,7 +210,6 @@ def connect(
            request_thread_pool=request_thread_pool,
            client_config=client_config,
            storage_options=storage_options,
-            read_consistency_interval=read_consistency_interval,
            **kwargs,
        )
    _check_s3_bucket_with_dots(str(uri), storage_options)
@@ -347,6 +336,7 @@ async def connect_async(
    host_override: str, optional
        The override url for LanceDB Cloud.
    read_consistency_interval: timedelta, default None
+        (For LanceDB OSS only)
        The interval at which to check for updates to the table from other
        processes. If None, then consistency is not checked. For performance
        reasons, this is the default. For strong consistency, set this to
@@ -356,10 +346,6 @@ async def connect_async(
        the last check, then the table will be checked for updates. Note: this
        consistency only applies to read operations. Write operations are
        always consistent.
-
-        Stronger consistency is not free. The smaller the interval, the more
-        often each read pays the cost of checking for updates against object
-        storage, raising per-read latency and cost.
    client_config: ClientConfig or dict, optional
        Configuration options for the LanceDB Cloud HTTP client. If a dict, then
        the keys are the attributes of the ClientConfig class. If None, then the
@@ -392,8 +378,6 @@ async def connect_async(
    ...     db = await lancedb.connect_async("s3://my-bucket/lancedb",
    ...                                      storage_options={
    ...                                          "aws_access_key_id": "***"})
-    ...     # For tests and temporary data, use an in-memory database
-    ...     db = await lancedb.connect_async("memory://")
    ...     # Connect to LanceDB cloud
    ...     db = await lancedb.connect_async("db://my_database", api_key="ldb_...",
    ...                                      client_config={
--- a/python/python/lancedb/db.py
+++ b/python/python/lancedb/db.py
@@ -8,17 +8,7 @@ from abc import abstractmethod
 from datetime import timedelta
 from pathlib import Path
 import sys
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Dict,
-    Generator,
-    Iterable,
-    List,
-    Literal,
-    Optional,
-    Union,
-)
+from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Literal, Optional, Union

 if sys.version_info >= (3, 12):
    from typing import override
@@ -323,7 +313,7 @@ class DBConnection(EnforceOverrides):
        >>> data = [{"vector": [1.1, 1.2], "lat": 45.5, "long": -122.7},
        ...         {"vector": [0.2, 1.8], "lat": 40.1, "long":  -74.1}]
        >>> db.create_table("my_table", data)
-        LanceTable(name='my_table', ...)
+        LanceTable(name='my_table', version=1, ...)
        >>> db["my_table"].head()
        pyarrow.Table
        vector: fixed_size_list<item: float>[2]
@@ -344,7 +334,7 @@ class DBConnection(EnforceOverrides):
        ...    "long": [-122.7, -74.1]
        ... })
        >>> db.create_table("table2", data)
-        LanceTable(name='table2', ...)
+        LanceTable(name='table2', version=1, ...)
        >>> db["table2"].head()
        pyarrow.Table
        vector: fixed_size_list<item: float>[2]
@@ -367,7 +357,7 @@ class DBConnection(EnforceOverrides):
        ...   pa.field("long", pa.float32())
        ... ])
        >>> db.create_table("table3", data, schema = custom_schema)
-        LanceTable(name='table3', ...)
+        LanceTable(name='table3', version=1, ...)
        >>> db["table3"].head()
        pyarrow.Table
        vector: fixed_size_list<item: float>[2]
@@ -401,7 +391,7 @@ class DBConnection(EnforceOverrides):
        ...     pa.field("price", pa.float32()),
        ... ])
        >>> db.create_table("table4", make_batches(), schema=schema)
-        LanceTable(name='table4', ...)
+        LanceTable(name='table4', version=1, ...)

        """
        raise NotImplementedError
@@ -578,15 +568,15 @@ class LanceDBConnection(DBConnection):
    >>> db = lancedb.connect("./.lancedb")
    >>> db.create_table("my_table", data=[{"vector": [1.1, 1.2], "b": 2},
    ...                                   {"vector": [0.5, 1.3], "b": 4}])
-    LanceTable(name='my_table', ...)
+    LanceTable(name='my_table', version=1, ...)
    >>> db.create_table("another_table", data=[{"vector": [0.4, 0.4], "b": 6}])
-    LanceTable(name='another_table', ...)
+    LanceTable(name='another_table', version=1, ...)
    >>> sorted(db.table_names())
    ['another_table', 'my_table']
    >>> len(db)
    2
    >>> db["my_table"]
-    LanceTable(name='my_table', ...)
+    LanceTable(name='my_table', version=1, ...)
    >>> "my_table" in db
    True
    >>> db.drop_table("my_table")
@@ -857,20 +847,11 @@ class LanceDBConnection(DBConnection):
            )
        )

-    def _all_table_names(self) -> Generator[str, None, None]:
-        page_token = None
-        while True:
-            response = self.list_tables(page_token=page_token)
-            yield from response.tables
-            page_token = response.page_token
-            if not page_token:
-                return
-
    def __len__(self) -> int:
-        return sum(1 for _ in self._all_table_names())
+        return len(self.table_names())

    def __contains__(self, name: str) -> bool:
-        return name in self._all_table_names()
+        return name in self.table_names()

    @override
    def create_table(
--- a/python/python/lancedb/query.py
+++ b/python/python/lancedb/query.py
@@ -3,14 +3,12 @@

 from __future__ import annotations

-import asyncio
 from abc import ABC, abstractmethod
 from concurrent.futures import ThreadPoolExecutor
-from datetime import timedelta
 from enum import Enum
+from datetime import timedelta
 from typing import (
    TYPE_CHECKING,
-    Any,
    Dict,
    List,
    Literal,
@@ -19,40 +17,41 @@ from typing import (
    Type,
    TypeVar,
    Union,
+    Any,
 )

+import asyncio
 import deprecation
 import numpy as np
 import pyarrow as pa
 import pyarrow.compute as pc
 import pydantic
-from typing_extensions import Annotated

-from lancedb._lancedb import fts_query_to_json
-from lancedb.background_loop import LOOP
 from lancedb.pydantic import PYDANTIC_VERSION
+from lancedb.background_loop import LOOP

 from . import __version__
 from .arrow import AsyncRecordBatchReader
 from .dependencies import pandas as pd
-from .expr import Expr
 from .rerankers.base import Reranker
 from .rerankers.rrf import RRFReranker
 from .rerankers.util import check_reranker_result
 from .util import flatten_columns
+from .expr import Expr
+from lancedb._lancedb import fts_query_to_json
+from typing_extensions import Annotated

 if TYPE_CHECKING:
    import sys
-
    import PIL
    import polars as pl

+    from ._lancedb import Query as LanceQuery
    from ._lancedb import FTSQuery as LanceFTSQuery
    from ._lancedb import HybridQuery as LanceHybridQuery
-    from ._lancedb import PyQueryRequest
-    from ._lancedb import Query as LanceQuery
-    from ._lancedb import TakeQuery as LanceTakeQuery
    from ._lancedb import VectorQuery as LanceVectorQuery
+    from ._lancedb import TakeQuery as LanceTakeQuery
+    from ._lancedb import PyQueryRequest
    from .common import VEC
    from .pydantic import LanceModel
    from .table import Table
@@ -3349,18 +3348,16 @@ class BaseQueryBuilder(object):
            If not specified, no timeout is applied. If the query does not
            complete within the specified time, an error will be raised.
        """
-        async_reader = LOOP.run(
-            self._inner.to_batches(max_batch_length=max_batch_length, timeout=timeout)
-        )
+        async_iter = LOOP.run(self._inner.execute(max_batch_length, timeout))

        def iter_sync():
            try:
                while True:
-                    yield LOOP.run(async_reader.__anext__())
+                    yield LOOP.run(async_iter.__anext__())
            except StopAsyncIteration:
                return

-        return pa.RecordBatchReader.from_batches(async_reader.schema, iter_sync())
+        return pa.RecordBatchReader.from_batches(async_iter.schema, iter_sync())

    def to_arrow(self, timeout: Optional[timedelta] = None) -> pa.Table:
        """
--- a/python/python/lancedb/remote/db.py
+++ b/python/python/lancedb/remote/db.py
@@ -50,7 +50,6 @@ class RemoteDBConnection(DBConnection):
        connection_timeout: Optional[float] = None,
        read_timeout: Optional[float] = None,
        storage_options: Optional[Dict[str, str]] = None,
-        read_consistency_interval: Optional[timedelta] = None,
    ):
        """Connect to a remote LanceDB database."""
        if isinstance(client_config, dict):
@@ -104,7 +103,6 @@ class RemoteDBConnection(DBConnection):
                host_override=host_override,
                client_config=client_config,
                storage_options=storage_options,
-                read_consistency_interval=read_consistency_interval,
            )
        )

--- a/python/python/lancedb/table.py
+++ b/python/python/lancedb/table.py
@@ -2178,7 +2178,7 @@ class LanceTable(Table):
        return LOOP.run(self._table.count_rows(filter))

    def __repr__(self) -> str:
-        val = f"{self.__class__.__name__}(name={self.name!r}"
+        val = f"{self.__class__.__name__}(name={self.name!r}, version={self.version}"
        if self._conn.read_consistency_interval is not None:
            val += ", read_consistency_interval={!r}".format(
                self._conn.read_consistency_interval
--- a/python/python/lancedb/util.py
+++ b/python/python/lancedb/util.py
@@ -10,7 +10,7 @@ import pathlib
 import warnings
 from datetime import date, datetime
 from functools import singledispatch
-from typing import Tuple, Union, Optional, Any, List
+from typing import Tuple, Union, Optional, Any
 from urllib.parse import urlparse

 import numpy as np
@@ -189,33 +189,7 @@ def flatten_columns(tbl: pa.Table, flatten: Optional[Union[int, bool]] = None):
    return tbl


-def _format_field_path(path: List[str]) -> str:
-    def format_segment(segment: str) -> str:
-        if all(char.isalnum() or char == "_" for char in segment):
-            return segment
-        return f"`{segment.replace('`', '``')}`"
-
-    return ".".join(format_segment(segment) for segment in path)
-
-
-def _iter_vector_columns(
-    field: pa.Field, path: List[str], dim: Optional[int] = None
-) -> List[str]:
-    field_path = [*path, field.name]
-    if is_vector_column(field.type):
-        vector_dim = infer_vector_column_dim(field.type)
-        if dim is None or vector_dim == dim:
-            return [_format_field_path(field_path)]
-        return []
-    if pa.types.is_struct(field.type):
-        columns = []
-        for idx in range(field.type.num_fields):
-            columns.extend(_iter_vector_columns(field.type.field(idx), field_path, dim))
-        return columns
-    return []
-
-
-def inf_vector_column_query(schema: pa.Schema, dim: Optional[int] = None) -> str:
+def inf_vector_column_query(schema: pa.Schema) -> str:
    """
    Get the vector column name

@@ -228,21 +202,26 @@ def inf_vector_column_query(schema: pa.Schema, dim: Optional[int] = None) -> str
    -------
    str: the vector column name.
    """
-    vector_col_names = []
-    for field in schema:
-        vector_col_names.extend(_iter_vector_columns(field, [], dim))
-    if len(vector_col_names) > 1:
-        raise ValueError(
-            "Schema has more than one vector column. "
-            "Please specify the vector column name "
-            f"for vector search. Candidates: {vector_col_names}"
-        )
-    if len(vector_col_names) == 0:
+    vector_col_name = ""
+    vector_col_count = 0
+    for field_name in schema.names:
+        field = schema.field(field_name)
+        if is_vector_column(field.type):
+            vector_col_count += 1
+            if vector_col_count > 1:
+                raise ValueError(
+                    "Schema has more than one vector column. "
+                    "Please specify the vector column name "
+                    "for vector search"
+                )
+            elif vector_col_count == 1:
+                vector_col_name = field_name
+    if vector_col_count == 0:
        raise ValueError(
            "There is no vector column in the data. "
            "Please specify the vector column name for vector search"
        )
-    return vector_col_names[0]
+    return vector_col_name


 def is_vector_column(data_type: pa.DataType) -> bool:
@@ -268,29 +247,6 @@ def is_vector_column(data_type: pa.DataType) -> bool:
    return False


-def infer_vector_column_dim(data_type: pa.DataType) -> Optional[int]:
-    if pa.types.is_fixed_size_list(data_type):
-        return data_type.list_size
-    if pa.types.is_list(data_type):
-        return infer_vector_column_dim(data_type.value_type)
-    return None
-
-
-def _query_vector_dim(query: Optional[Any]) -> Optional[int]:
-    if query is None:
-        return None
-    if isinstance(query, np.ndarray):
-        if query.ndim == 0:
-            return None
-        return query.shape[-1]
-    if isinstance(query, list) and query:
-        first = query[0]
-        if isinstance(first, (list, tuple, np.ndarray)):
-            return len(first)
-        return len(query)
-    return None
-
-
 def infer_vector_column_name(
    schema: pa.Schema,
    query_type: str,
@@ -306,9 +262,7 @@ def infer_vector_column_name(

    if query is not None or query_type == "hybrid":
        try:
-            vector_column_name = inf_vector_column_query(
-                schema, dim=_query_vector_dim(query)
-            )
+            vector_column_name = inf_vector_column_query(schema)
        except Exception as e:
            raise e

--- a/python/python/tests/test_db.py
+++ b/python/python/tests/test_db.py
@@ -6,7 +6,6 @@ import re
 import sys
 from datetime import timedelta
 import os
-from types import SimpleNamespace

 import lancedb
 import numpy as np
@@ -189,43 +188,6 @@ def test_table_names(tmp_db: lancedb.DBConnection):
    assert len(result) == 3


-def test_db_contains_and_len_include_all_table_name_pages(tmp_db: lancedb.DBConnection):
-    for idx in range(20):
-        tmp_db.create_table(f"table_{idx}", data=[{"id": idx}])
-
-    assert len(tmp_db) == 20
-    for idx in range(20):
-        assert f"table_{idx}" in tmp_db
-    assert "does_not_exist" not in tmp_db
-
-
-def test_db_contains_stops_after_matching_table_page(
-    tmp_db: lancedb.DBConnection, monkeypatch
-):
-    calls = []
-    pages = {
-        None: SimpleNamespace(tables=["table_0", "table_1"], page_token="next"),
-        "next": SimpleNamespace(tables=["table_2"], page_token=None),
-    }
-
-    def list_tables(*, page_token=None, **_kwargs):
-        calls.append(page_token)
-        return pages[page_token]
-
-    monkeypatch.setattr(tmp_db, "list_tables", list_tables)
-
-    assert "table_1" in tmp_db
-    assert calls == [None]
-
-    calls.clear()
-    assert "table_2" in tmp_db
-    assert calls == [None, "next"]
-
-    calls.clear()
-    assert len(tmp_db) == 3
-    assert calls == [None, "next"]
-
-
@pytest.mark.asyncio
 async def test_table_names_async(tmp_path):
    db = lancedb.connect(tmp_path)
--- a/python/python/tests/test_fts.py
+++ b/python/python/tests/test_fts.py
@@ -563,7 +563,7 @@ def test_create_index_multiple_columns(tmp_path, table):


 def test_nested_schema(tmp_path, table):
-    table.create_fts_index("nested.text", with_position=True)
+    table.create_fts_index("nested.text")
    indices = table.list_indices()
    assert len(indices) == 1
    assert indices[0].index_type == "FTS"
@@ -577,98 +577,6 @@ def test_nested_schema(tmp_path, table):
    assert len(results) > 0
    assert all("puppy" in row["nested"]["text"] for row in results)

-    results = table.search(MatchQuery("puppy", "nested.text")).limit(5).to_list()
-    assert len(results) > 0
-    assert all("puppy" in row["nested"]["text"] for row in results)
-
-    phrase_results = (
-        table.search(PhraseQuery("puppy runs", "nested.text")).limit(5).to_list()
-    )
-    assert len(phrase_results) > 0
-    assert all("puppy runs" in row["nested"]["text"] for row in phrase_results)
-
-    hybrid_results = (
-        table.search(query_type="hybrid", fts_columns="nested.text")
-        .vector([0 for _ in range(128)])
-        .text("puppy")
-        .limit(5)
-        .to_list()
-    )
-    assert len(hybrid_results) > 0
-
-
-@pytest.mark.asyncio
-async def test_nested_schema_async(async_table):
-    await async_table.create_index("nested.text", config=FTS(with_position=True))
-    indices = await async_table.list_indices()
-    assert len(indices) == 1
-    assert indices[0].index_type == "FTS"
-    assert indices[0].columns == ["nested.text"]
-
-    results = await (
-        async_table.query()
-        .nearest_to_text("puppy", columns="nested.text")
-        .limit(5)
-        .to_list()
-    )
-    assert len(results) > 0
-    assert all("puppy" in row["nested"]["text"] for row in results)
-
-    results = await (
-        async_table.query()
-        .nearest_to_text(MatchQuery("puppy", "nested.text"))
-        .limit(5)
-        .to_list()
-    )
-    assert len(results) > 0
-    assert all("puppy" in row["nested"]["text"] for row in results)
-
-    phrase_results = await (
-        async_table.query()
-        .nearest_to_text(PhraseQuery("puppy runs", "nested.text"))
-        .limit(5)
-        .to_list()
-    )
-    assert len(phrase_results) > 0
-    assert all("puppy runs" in row["nested"]["text"] for row in phrase_results)
-
-    hybrid_results = await (
-        async_table.query()
-        .nearest_to([0 for _ in range(128)])
-        .nearest_to_text("puppy", columns="nested.text")
-        .limit(5)
-        .to_list()
-    )
-    assert len(hybrid_results) > 0
-
-
-def test_nested_schema_rejects_invalid_fts_fields(tmp_path):
-    db = ldb.connect(tmp_path)
-    data = pa.table(
-        {
-            "payload": pa.array(
-                [
-                    {"text": "puppy runs", "count": 1},
-                    {"text": "car drives", "count": 2},
-                ]
-            ),
-            "vector": pa.array(
-                [[0.1, 0.1], [0.2, 0.2]],
-                type=pa.list_(pa.float32(), list_size=2),
-            ),
-        }
-    )
-    table = db.create_table("test", data=data)
-
-    with pytest.raises(ValueError, match="FTS index cannot be created.*payload"):
-        table.create_fts_index("payload")
-
-    with pytest.raises(ValueError, match="FTS index cannot be created.*count"):
-        table.create_fts_index("payload.count")
-
-    with pytest.raises(ValueError, match="Field path `payload.missing` not found"):
-        table.create_fts_index("payload.missing")
-

 def test_search_index_with_filter(table):
    table.create_fts_index("text")
--- a/python/python/tests/test_index.py
+++ b/python/python/tests/test_index.py
@@ -105,46 +105,6 @@ async def test_create_scalar_index(some_table: AsyncTable):
    assert len(indices) == 0


-@pytest.mark.asyncio
-async def test_create_nested_scalar_index_lists_canonical_paths(db_async):
-    metadata_type = pa.struct(
-        [
-            pa.field("user_id", pa.int32()),
-            pa.field("user.id", pa.int32()),
-        ]
-    )
-    data = pa.Table.from_arrays(
-        [
-            pa.array([1, 2, 3], type=pa.int32()),
-            pa.array(
-                [
-                    {"user_id": 10, "user.id": 100},
-                    {"user_id": 20, "user.id": 200},
-                    {"user_id": 30, "user.id": 300},
-                ],
-                type=metadata_type,
-            ),
-        ],
-        names=["user_id", "metadata"],
-    )
-    table = await db_async.create_table("nested_scalar_index", data)
-
-    await table.create_index("user_id", config=BTree(), name="top_user_id_idx")
-    await table.create_index(
-        "metadata.user_id", config=BTree(), name="nested_user_id_idx"
-    )
-    await table.create_index(
-        "metadata.`user.id`", config=BTree(), name="escaped_user_id_idx"
-    )
-
-    columns_by_name = {
-        index.name: index.columns for index in await table.list_indices()
-    }
-    assert columns_by_name["top_user_id_idx"] == ["user_id"]
-    assert columns_by_name["nested_user_id_idx"] == ["metadata.user_id"]
-    assert columns_by_name["escaped_user_id_idx"] == ["metadata.`user.id`"]
-
-
@pytest.mark.asyncio
 async def test_create_fixed_size_binary_index(some_table: AsyncTable):
    await some_table.create_index("fsb", config=BTree())
--- a/python/python/tests/test_query.py
+++ b/python/python/tests/test_query.py
@@ -1512,37 +1512,6 @@ def test_take_queries(tmp_path):
    ]


-def test_take_queries_to_batches(tmp_path):
-    # Regression test for the sync take-query path: `to_batches` previously
-    # raised ``AttributeError: 'AsyncTakeQuery' object has no attribute
-    # 'execute'`` because the inherited ``BaseQueryBuilder.to_batches`` called
-    # ``execute`` on the async wrapper instead of the native query.
-    db = lancedb.connect(tmp_path)
-    data = pa.table({"idx": list(range(100)), "label": [str(i) for i in range(100)]})
-    table = db.create_table("test", data)
-
-    # Take by offset → to_batches
-    rs = list(table.take_offsets([5, 2, 17]).to_batches())
-    assert all(isinstance(b, pa.RecordBatch) for b in rs)
-    assert sum(b.num_rows for b in rs) == 3
-    assert sorted(v for b in rs for v in b.column("idx").to_pylist()) == [2, 5, 17]
-
-    # Take by row id → to_batches
-    rs = list(table.take_row_ids([5, 2, 17]).to_batches())
-    assert all(isinstance(b, pa.RecordBatch) for b in rs)
-    assert sum(b.num_rows for b in rs) == 3
-    assert sorted(v for b in rs for v in b.column("idx").to_pylist()) == [2, 5, 17]
-
-    # Take with select projection → to_batches preserves the projection
-    rs = list(table.take_row_ids([5, 2, 17]).select(["label"]).to_batches())
-    assert all(b.schema.names == ["label"] for b in rs)
-    assert sorted(v for b in rs for v in b.column("label").to_pylist()) == [
-        "17",
-        "2",
-        "5",
-    ]
-
-
 def test_getitems(tmp_path):
    db = lancedb.connect(tmp_path)
    data = pa.table(
--- a/python/python/tests/test_remote_db.py
+++ b/python/python/tests/test_remote_db.py
@@ -362,22 +362,6 @@ def test_table_create_indices():
                    schema=dict(
                        fields=[
                            dict(name="id", type={"type": "int64"}, nullable=False),
-                            dict(name="text", type={"type": "string"}, nullable=False),
-                            dict(
-                                name="vector",
-                                type={
-                                    "type": "fixed_size_list",
-                                    "fields": [
-                                        dict(
-                                            name="item",
-                                            type={"type": "float"},
-                                            nullable=True,
-                                        )
-                                    ],
-                                    "length": 2,
-                                },
-                                nullable=False,
-                            ),
                        ]
                    ),
                )
--- a/python/python/tests/test_table.py
+++ b/python/python/tests/test_table.py
@@ -33,7 +33,7 @@ def test_basic(mem_db: DBConnection):
    table = mem_db.create_table("test", data=data)

    assert table.name == "test"
-    assert "LanceTable(name='test', _conn=LanceDBConnection(" in repr(table)
+    assert "LanceTable(name='test', version=1, _conn=LanceDBConnection(" in repr(table)
    expected_schema = pa.schema(
        {
            "vector": pa.list_(pa.float32(), 2),
@@ -1934,10 +1934,6 @@ def test_create_index_nested_field_paths(mem_db: DBConnection):
    assert len(vector_results) == 1
    assert vector_results[0]["metadata"]["user_id"] == 0

-    default_vector_results = table.search([0.0, 1.0]).limit(1).to_list()
-    assert len(default_vector_results) == 1
-    assert default_vector_results[0]["metadata"]["user_id"] == 0
-
    filtered_results = table.search().where("metadata.user_id = 42").limit(1).to_list()
    assert len(filtered_results) == 1
    assert filtered_results[0]["metadata"]["user_id"] == 42
@@ -2017,74 +2013,6 @@ def test_search_with_schema_inf_multiple_vector(mem_db: DBConnection):
        table.search(q).limit(1).to_arrow()


-def test_search_infers_single_nested_vector(mem_db: DBConnection):
-    schema = pa.schema(
-        [
-            pa.field("id", pa.int32()),
-            pa.field(
-                "image",
-                pa.struct([pa.field("embedding", pa.list_(pa.float32(), 2))]),
-            ),
-        ]
-    )
-    data = pa.Table.from_pylist(
-        [
-            {"id": 0, "image": {"embedding": [0.0, 1.0]}},
-            {"id": 1, "image": {"embedding": [10.0, 11.0]}},
-        ],
-        schema=schema,
-    )
-    table = mem_db.create_table("nested_vector_default_search", data=data)
-
-    result = table.search([0.0, 1.0]).limit(1).to_list()
-    assert result[0]["id"] == 0
-
-
-def test_search_nested_vector_multiple_candidates(mem_db: DBConnection):
-    schema = pa.schema(
-        [
-            pa.field(
-                "image",
-                pa.struct([pa.field("embedding", pa.list_(pa.float32(), 2))]),
-            ),
-            pa.field(
-                "text",
-                pa.struct([pa.field("embedding", pa.list_(pa.float32(), 2))]),
-            ),
-        ]
-    )
-    data = pa.Table.from_pylist(
-        [
-            {
-                "image": {"embedding": [0.0, 1.0]},
-                "text": {"embedding": [2.0, 3.0]},
-            }
-        ],
-        schema=schema,
-    )
-    table = mem_db.create_table("nested_vector_multiple_candidates", data=data)
-
-    with pytest.raises(ValueError, match="image.embedding.*text.embedding"):
-        table.search([0.0, 1.0]).limit(1).to_arrow()
-
-
-def test_search_nested_vector_no_candidates(mem_db: DBConnection):
-    schema = pa.schema(
-        [
-            pa.field("id", pa.int32()),
-            pa.field("metadata", pa.struct([pa.field("label", pa.string())])),
-        ]
-    )
-    data = pa.Table.from_pylist(
-        [{"id": 0, "metadata": {"label": "cat"}}],
-        schema=schema,
-    )
-    table = mem_db.create_table("nested_vector_no_candidates", data=data)
-
-    with pytest.raises(ValueError, match="no vector column"):
-        table.search([0.0, 1.0]).limit(1).to_arrow()
-
-
 def test_compact_cleanup(tmp_db: DBConnection):
    pytest.importorskip("lance")
    table = tmp_db.create_table(
--- a/rust/lancedb/Cargo.toml
+++ b/rust/lancedb/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.30.0-beta.1"
+version = "0.29.1-beta.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -104,7 +104,6 @@ datafusion.workspace = true
 http-body = "1"                                        # Matching reqwest
 rstest = "0.23.0"
 test-log = "0.2"
-serial_test = "3"


 [features]
--- a/rust/lancedb/src/connection.rs
+++ b/rust/lancedb/src/connection.rs
@@ -812,7 +812,8 @@ impl ConnectBuilder {
        self
    }

-    /// The interval at which to check for updates from other processes.
+    /// The interval at which to check for updates from other processes. This
+    /// only affects LanceDB OSS.
    ///
    /// If left unset, consistency is not checked. For maximum read
    /// performance, this is the default. For strong consistency, set this to
@@ -824,11 +825,8 @@ impl ConnectBuilder {
    /// This only affects read operations. Write operations are always
    /// consistent.
    ///
-    /// # Cost
-    ///
-    /// Stronger consistency is not free. The smaller the interval, the more
-    /// often each read pays the cost of checking for updates against object
-    /// storage, raising per-read latency and cost.
+    /// LanceDB Cloud uses eventual consistency under the hood, and is not
+    /// currently configurable.
    pub fn read_consistency_interval(
        mut self,
        read_consistency_interval: std::time::Duration,
@@ -888,7 +886,6 @@ impl ConnectBuilder {
            options.host_override,
            self.request.client_config,
            storage_options.into(),
-            self.request.read_consistency_interval,
        )?);
        Ok(Connection {
            internal,
--- a/rust/lancedb/src/index/vector.rs
+++ b/rust/lancedb/src/index/vector.rs
@@ -23,12 +23,17 @@ impl VectorIndex {
            .fields
            .iter()
            .map(|field_id| {
-                manifest.schema.field_path(*field_id).unwrap_or_else(|_| {
-                    panic!(
-                        "field {field_id} of index {} must exist in schema",
-                        index.name
-                    )
-                })
+                manifest
+                    .schema
+                    .field_by_id(*field_id)
+                    .unwrap_or_else(|| {
+                        panic!(
+                            "field {field_id} of index {} must exist in schema",
+                            index.name
+                        )
+                    })
+                    .name
+                    .clone()
            })
            .collect();
        Self {
--- a/rust/lancedb/src/remote/client.rs
+++ b/rust/lancedb/src/remote/client.rs
@@ -245,9 +245,6 @@ pub struct RestfulLanceDbClient<S: HttpSend = Sender> {
    pub(crate) sender: S,
    pub(crate) id_delimiter: String,
    pub(crate) header_provider: Option<Arc<dyn HeaderProvider>>,
-    /// Connection-level read consistency interval. Drives the
-    /// `x-lancedb-min-timestamp` freshness header sent on read requests.
-    pub(crate) read_consistency_interval: Option<Duration>,
 }

 impl<S: HttpSend> std::fmt::Debug for RestfulLanceDbClient<S> {
@@ -341,7 +338,6 @@ impl RestfulLanceDbClient<Sender> {
        host_override: Option<String>,
        default_headers: HeaderMap,
        client_config: ClientConfig,
-        read_consistency_interval: Option<Duration>,
    ) -> Result<Self> {
        // Get the timeouts
        let timeout =
@@ -439,7 +435,6 @@ impl RestfulLanceDbClient<Sender> {
                .clone()
                .unwrap_or("$".to_string()),
            header_provider: client_config.header_provider,
-            read_consistency_interval,
        })
    }
 }
@@ -845,16 +840,6 @@ pub mod test_utils {
    pub fn client_with_handler<T>(
        handler: impl Fn(reqwest::Request) -> http::response::Response<T> + Send + Sync + 'static,
    ) -> RestfulLanceDbClient<MockSender>
-    where
-        T: Into<reqwest::Body>,
-    {
-        client_with_handler_and_interval(handler, None)
-    }
-
-    pub fn client_with_handler_and_interval<T>(
-        handler: impl Fn(reqwest::Request) -> http::response::Response<T> + Send + Sync + 'static,
-        read_consistency_interval: Option<Duration>,
-    ) -> RestfulLanceDbClient<MockSender>
    where
        T: Into<reqwest::Body>,
    {
@@ -872,7 +857,6 @@ pub mod test_utils {
            },
            id_delimiter: "$".to_string(),
            header_provider: None,
-            read_consistency_interval,
        }
    }

@@ -897,7 +881,6 @@ pub mod test_utils {
            },
            id_delimiter: config.id_delimiter.unwrap_or_else(|| "$".to_string()),
            header_provider: config.header_provider,
-            read_consistency_interval: None,
        }
    }
 }
@@ -905,7 +888,6 @@ pub mod test_utils {
 #[cfg(test)]
 mod tests {
    use super::*;
-    use serial_test::serial;
    use std::time::Duration;

    #[test]
@@ -1064,7 +1046,6 @@ mod tests {
            sender: Sender,
            id_delimiter: "+".to_string(),
            header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
-            read_consistency_interval: None,
        };

        // Apply dynamic headers
@@ -1100,7 +1081,6 @@ mod tests {
            sender: Sender,
            id_delimiter: "+".to_string(),
            header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
-            read_consistency_interval: None,
        };

        // Apply dynamic headers
@@ -1138,7 +1118,6 @@ mod tests {
            sender: Sender,
            id_delimiter: "+".to_string(),
            header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
-            read_consistency_interval: None,
        };

        // Header provider errors should fail the request
@@ -1164,7 +1143,6 @@ mod tests {
    }

    #[test]
-    #[serial(user_id_env)]
    fn test_resolve_user_id_none() {
        let config = ClientConfig::default();
        // Clear env vars that might be set from other tests
@@ -1177,7 +1155,6 @@ mod tests {
    }

    #[test]
-    #[serial(user_id_env)]
    fn test_resolve_user_id_from_env() {
        // SAFETY: This is only called in tests
        unsafe {
@@ -1192,7 +1169,6 @@ mod tests {
    }

    #[test]
-    #[serial(user_id_env)]
    fn test_resolve_user_id_from_env_key() {
        // SAFETY: This is only called in tests
        unsafe {
@@ -1213,7 +1189,6 @@ mod tests {
    }

    #[test]
-    #[serial(user_id_env)]
    fn test_resolve_user_id_direct_takes_precedence() {
        // SAFETY: This is only called in tests
        unsafe {
@@ -1231,7 +1206,6 @@ mod tests {
    }

    #[test]
-    #[serial(user_id_env)]
    fn test_resolve_user_id_empty_env_ignored() {
        // SAFETY: This is only called in tests
        unsafe {
--- a/rust/lancedb/src/remote/db.rs
+++ b/rust/lancedb/src/remote/db.rs
@@ -206,7 +206,6 @@ impl RemoteDatabase {
        host_override: Option<String>,
        client_config: ClientConfig,
        options: RemoteOptions,
-        read_consistency_interval: Option<std::time::Duration>,
    ) -> Result<Self> {
        let parsed = super::client::parse_db_url(uri)?;
        let header_map = RestfulLanceDbClient::<Sender>::default_headers(
@@ -234,7 +233,6 @@ impl RemoteDatabase {
            host_override,
            header_map,
            client_config.clone(),
-            read_consistency_interval,
        )?;

        let table_cache = Cache::builder()
--- a/rust/lancedb/src/remote/table.rs
+++ b/rust/lancedb/src/remote/table.rs
--- a/rust/lancedb/src/table.rs
+++ b/rust/lancedb/src/table.rs
@@ -656,30 +656,6 @@ mod test_utils {
            }
        }

-        pub fn new_with_handler_and_interval<T>(
-            name: impl Into<String>,
-            handler: impl Fn(reqwest::Request) -> http::Response<T> + Clone + Send + Sync + 'static,
-            read_consistency_interval: Option<std::time::Duration>,
-        ) -> Self
-        where
-            T: Into<reqwest::Body>,
-        {
-            let inner = Arc::new(
-                crate::remote::table::RemoteTable::new_mock_with_consistency_interval(
-                    name.into(),
-                    handler.clone(),
-                    read_consistency_interval,
-                ),
-            );
-            let database = Arc::new(crate::remote::db::RemoteDatabase::new_mock(handler));
-            Self {
-                inner,
-                database: Some(database),
-                // Registry is unused.
-                embedding_registry: Arc::new(MemoryRegistry::new()),
-            }
-        }
-
        pub fn new_with_handler_version<T>(
            name: impl Into<String>,
            version: semver::Version,
@@ -2712,13 +2688,16 @@ impl BaseTable for NativeTable {
                message: "Multi-column (composite) indices are not yet supported".to_string(),
            });
        }
-        self.dataset.ensure_mutable()?;
-        let mut dataset = (*self.dataset.get().await?).clone();
+
+        let dataset = self.dataset.get().await?;
        let (column, field) = Self::resolve_index_field(dataset.schema(), &opts.columns[0])?;
+        drop(dataset);

        let lance_idx_params = self.make_index_params(&field, opts.index.clone()).await?;
        let index_type = self.get_index_type_for_field(&field, &opts.index);
        let columns = [column.as_str()];
+        self.dataset.ensure_mutable()?;
+        let mut dataset = (*self.dataset.get().await?).clone();
        let mut builder = dataset
            .create_index_builder(&columns, index_type, lance_idx_params.as_ref())
            .train(opts.train)
@@ -2836,88 +2815,63 @@ impl BaseTable for NativeTable {
    async fn list_indices(&self) -> Result<Vec<IndexConfig>> {
        let dataset = self.dataset.get().await?;
        let indices = dataset.load_indices().await?;
-        let results = futures::stream::iter(indices.as_slice())
-            .then(|idx| async {
-                // skip Lance internal indexes
-                if idx.name == FRAG_REUSE_INDEX_NAME {
+        let results = futures::stream::iter(indices.as_slice()).then(|idx| async {
+
+            // skip Lance internal indexes
+            if idx.name == FRAG_REUSE_INDEX_NAME {
+                return None;
+            }
+
+            let stats = match dataset.index_statistics(idx.name.as_str()).await {
+                Ok(stats) => stats,
+                Err(e) => {
+                    log::warn!("Failed to get statistics for index {} ({}): {}", idx.name, idx.uuid, e);
                    return None;
                }
+            };

-                let stats = match dataset.index_statistics(idx.name.as_str()).await {
-                    Ok(stats) => stats,
-                    Err(e) => {
-                        log::warn!(
-                            "Failed to get statistics for index {} ({}): {}",
-                            idx.name,
-                            idx.uuid,
-                            e
-                        );
-                        return None;
-                    }
-                };
-
-                let stats: serde_json::Value = match serde_json::from_str(&stats) {
-                    Ok(stats) => stats,
-                    Err(e) => {
-                        log::warn!(
-                            "Failed to deserialize index statistics for index {} ({}): {}",
-                            idx.name,
-                            idx.uuid,
-                            e
-                        );
-                        return None;
-                    }
-                };
-
-                let Some(index_type) = stats.get("index_type").and_then(|v| v.as_str()) else {
-                    log::warn!(
-                        "Index statistics was missing 'index_type' field for index {} ({})",
-                        idx.name,
-                        idx.uuid
-                    );
+            let stats: serde_json::Value = match serde_json::from_str(&stats) {
+                Ok(stats) => stats,
+                Err(e) => {
+                    log::warn!("Failed to deserialize index statistics for index {} ({}): {}", idx.name, idx.uuid, e);
                    return None;
-                };
+                }
+            };

-                let index_type: crate::index::IndexType = match index_type.parse() {
-                    Ok(index_type) => index_type,
+            let Some(index_type) = stats.get("index_type").and_then(|v| v.as_str()) else {
+                log::warn!("Index statistics was missing 'index_type' field for index {} ({})", idx.name, idx.uuid);
+                return None;
+            };
+
+            let index_type: crate::index::IndexType = match index_type.parse() {
+                Ok(index_type) => index_type,
+                Err(e) => {
+                    log::warn!("Failed to parse index type for index {} ({}): {}", idx.name, idx.uuid, e);
+                    return None;
+                }
+            };
+
+            let mut columns = Vec::with_capacity(idx.fields.len());
+            for field_id in &idx.fields {
+                let column = match dataset.schema().field_path(*field_id) {
+                    Ok(column) => column,
                    Err(e) => {
                        log::warn!(
-                            "Failed to parse index type for index {} ({}): {}",
+                            "The index {} ({}) referenced a field with id {} which does not exist in the schema: {}",
                            idx.name,
                            idx.uuid,
+                            field_id,
                            e
                        );
                        return None;
                    }
                };
+                columns.push(column);
+            }

-                let mut columns = Vec::with_capacity(idx.fields.len());
-                for field_id in &idx.fields {
-                    let field_path = match dataset.schema().field_path(*field_id) {
-                        Ok(field_path) => field_path,
-                        Err(e) => {
-                            log::warn!(
-                                "Failed to resolve field path for index {} ({}) field id {}: {}",
-                                idx.name,
-                                idx.uuid,
-                                field_id,
-                                e
-                            );
-                            return None;
-                        }
-                    };
-                    columns.push(field_path);
-                }
-
-                let name = idx.name.clone();
-                Some(IndexConfig {
-                    index_type,
-                    columns,
-                    name,
-                })
-            })
-            .collect::<Vec<_>>()
-            .await;
+            let name = idx.name.clone();
+            Some(IndexConfig { index_type, columns, name })
+        }).collect::<Vec<_>>().await;

        Ok(results.into_iter().flatten().collect())
    }
@@ -3120,7 +3074,6 @@ pub struct FragmentSummaryStats {
 #[cfg(test)]
 #[allow(deprecated)]
 mod tests {
-    use std::collections::HashMap;
    use std::sync::Arc;
    use std::sync::atomic::{AtomicBool, Ordering};
    use std::time::Duration;
@@ -3901,25 +3854,6 @@ mod tests {
            1
        );

-        let default_vector_results = table
-            .query()
-            .nearest_to(&[0.0; 8])
-            .unwrap()
-            .limit(1)
-            .execute()
-            .await
-            .unwrap()
-            .try_collect::<Vec<_>>()
-            .await
-            .unwrap();
-        assert_eq!(
-            default_vector_results
-                .iter()
-                .map(|batch| batch.num_rows())
-                .sum::<usize>(),
-            1
-        );
-
        let fts_results = table
            .query()
            .full_text_search(FullTextSearchQuery::new("document".to_string()))
--- a/rust/lancedb/src/utils/mod.rs
+++ b/rust/lancedb/src/utils/mod.rs
@@ -6,7 +6,7 @@ pub(crate) mod background_cache;
 use std::sync::Arc;

 use arrow_array::RecordBatch;
-use arrow_schema::{DataType, Field, Schema, SchemaRef};
+use arrow_schema::{DataType, Schema, SchemaRef};
 use datafusion_common::{DataFusionError, Result as DataFusionResult};
 use datafusion_execution::RecordBatchStream;
 use futures::{FutureExt, Stream};
@@ -152,10 +152,14 @@ pub fn validate_namespace(namespace: &[String]) -> Result<()> {
 /// Find one default column to create index or perform vector query.
 pub(crate) fn default_vector_column(schema: &Schema, dim: Option<i32>) -> Result<String> {
    // Try to find a vector column.
-    let mut candidates = Vec::new();
-    for field in schema.fields() {
-        collect_vector_columns(field, &mut Vec::new(), dim, &mut candidates);
-    }
+    let candidates = schema
+        .fields()
+        .iter()
+        .filter_map(|field| match infer_vector_dim(field.data_type()) {
+            Ok(d) if dim.is_none() || dim == Some(d as i32) => Some(field.name()),
+            _ => None,
+        })
+        .collect::<Vec<_>>();
    if candidates.is_empty() {
        Err(Error::InvalidInput {
            message: format!(
@@ -176,57 +180,6 @@ pub(crate) fn default_vector_column(schema: &Schema, dim: Option<i32>) -> Result
    }
 }

-fn collect_vector_columns(
-    field: &Field,
-    path: &mut Vec<String>,
-    dim: Option<i32>,
-    candidates: &mut Vec<String>,
-) {
-    path.push(field.name().clone());
-    match infer_vector_dim(field.data_type()) {
-        Ok(d) if dim.is_none() || dim == Some(d as i32) => {
-            let path_segments = path.iter().map(String::as_str).collect::<Vec<_>>();
-            candidates.push(lance_core::datatypes::format_field_path(&path_segments));
-        }
-        _ => {
-            if let DataType::Struct(fields) = field.data_type() {
-                for child in fields {
-                    collect_vector_columns(child, path, dim, candidates);
-                }
-            }
-        }
-    }
-    path.pop();
-}
-
-pub(crate) fn resolve_arrow_field_path(schema: &Schema, column: &str) -> Result<(String, Field)> {
-    lance_core::datatypes::parse_field_path(column).map_err(|e| Error::InvalidInput {
-        message: format!("Invalid field path `{}`: {}", column, e),
-    })?;
-
-    let lance_schema =
-        lance_core::datatypes::Schema::try_from(schema).map_err(|e| Error::Schema {
-            message: format!("Invalid schema: {}", e),
-        })?;
-    let field_path = lance_schema
-        .resolve_case_insensitive(column)
-        .ok_or_else(|| Error::Schema {
-            message: format!(
-                "Field path `{}` not found in schema. Available field paths: {}",
-                column,
-                lance_schema.field_paths().join(", ")
-            ),
-        })?;
-    let field = field_path.last().expect("field path should be non-empty");
-    let path_segments = field_path
-        .iter()
-        .map(|field| field.name.as_str())
-        .collect::<Vec<_>>();
-    let canonical_path = lance_core::datatypes::format_field_path(&path_segments);
-
-    Ok((canonical_path, Field::from(*field)))
-}
-
 pub fn supported_btree_data_type(dtype: &DataType) -> bool {
    dtype.is_integer()
        || dtype.is_floating()
@@ -497,49 +450,6 @@ mod tests {
            "vec"
        );

-        let schema_with_nested_vec_col = Schema::new(vec![
-            Field::new("id", DataType::Int16, true),
-            Field::new(
-                "image",
-                DataType::Struct(
-                    vec![Field::new(
-                        "embedding",
-                        DataType::FixedSizeList(
-                            Arc::new(Field::new("item", DataType::Float32, false)),
-                            10,
-                        ),
-                        false,
-                    )]
-                    .into(),
-                ),
-                false,
-            ),
-        ]);
-        assert_eq!(
-            default_vector_column(&schema_with_nested_vec_col, None).unwrap(),
-            "image.embedding"
-        );
-
-        let schema_with_escaped_nested_vec_col = Schema::new(vec![Field::new(
-            "image-meta",
-            DataType::Struct(
-                vec![Field::new(
-                    "embedding.v1",
-                    DataType::FixedSizeList(
-                        Arc::new(Field::new("item", DataType::Float32, false)),
-                        10,
-                    ),
-                    false,
-                )]
-                .into(),
-            ),
-            false,
-        )]);
-        assert_eq!(
-            default_vector_column(&schema_with_escaped_nested_vec_col, None).unwrap(),
-            "`image-meta`.`embedding.v1`"
-        );
-
        let multi_vec_col = Schema::new(vec![
            Field::new("id", DataType::Int16, true),
            Field::new(
@@ -559,48 +469,6 @@ mod tests {
                .to_string()
                .contains("More than one")
        );
-
-        let multi_nested_vec_col = Schema::new(vec![
-            Field::new(
-                "image",
-                DataType::Struct(
-                    vec![Field::new(
-                        "embedding",
-                        DataType::FixedSizeList(
-                            Arc::new(Field::new("item", DataType::Float32, false)),
-                            10,
-                        ),
-                        false,
-                    )]
-                    .into(),
-                ),
-                false,
-            ),
-            Field::new(
-                "text",
-                DataType::Struct(
-                    vec![Field::new(
-                        "embedding",
-                        DataType::FixedSizeList(
-                            Arc::new(Field::new("item", DataType::Float32, false)),
-                            50,
-                        ),
-                        false,
-                    )]
-                    .into(),
-                ),
-                false,
-            ),
-        ]);
-        assert_eq!(
-            default_vector_column(&multi_nested_vec_col, Some(50)).unwrap(),
-            "text.embedding"
-        );
-        let err = default_vector_column(&multi_nested_vec_col, None)
-            .unwrap_err()
-            .to_string();
-        assert!(err.contains("image.embedding"));
-        assert!(err.contains("text.embedding"));
    }

    #[test]