chore: update lance dependency to v12.0.0-beta.18

this PR blob v2 field helpers and reads to the Node SDK.

`blob()` marks a field as blob v2 and lets you set the storage
thresholds. Inputs can be bytes, a URI, or a data/uri struct.

Queries return descriptors. `fetchBlobs()` reads the bytes by row ID,
and `fetchBlobFiles()` gives you lazy handles for full or range reads.
`blobColumns()` lists the blob fields, including nested ones.

Fetch uses the table’s current checkout. It preserves order, duplicates,
and nulls. Holding row IDs across compaction still requires stable row
IDs.

```javascript
const db = await connect("./data");
const video = await readFile("clip.mp4");
const table = await db.createTable(
  "videos",
  [{ id: 1n, video }],
  {
    schema: new Schema([
      new Field("id", new Int64()),
      blob("video"),
    ]),
  },
);
const rows = await table.query().select(["id"]).withRowId().toArray();
const rowIds = rows.map((row) => row._rowid as bigint);
const bytes = await table.fetchBlobs("video", rowIds);
const [handle] = await table.fetchBlobFiles("video", rowIds);
const header = await handle!.readRange(0n, 65536n);

```

### Testing

- cover input validation, thresholds, nested fields, fetch ordering,
nulls, and range reads.

Cargo.toml

@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 
 [workspace.dependencies]
-lance = { "version" = "=12.0.0-beta.15", default-features = false, "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=12.0.0-beta.15", default-features = false, "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=12.0.0-beta.15", default-features = false, "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=12.0.0-beta.15", "tag" = "v12.0.0-beta.15", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=12.0.0-beta.18", default-features = false, "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=12.0.0-beta.18", default-features = false, "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=12.0.0-beta.18", default-features = false, "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=12.0.0-beta.18", "tag" = "v12.0.0-beta.18", "git" = "https://github.com/lance-format/lance.git" }
 lancedb = { path = "rust/lancedb", default-features = false }
 ahash = "0.8"
 # Note that this one does not include pyarrow
@@ -60,7 +60,7 @@ log = "0.4"
 metrics = "0.24"
 metrics-util = "0.19"
 moka = { version = "0.12", features = ["future"] }
-object_store = "0.13.2"
+object_store = "0.14.1"
 pin-project = "1.0.7"
 rand = "0.9"
 snafu = "0.8"

docs/src/js/classes/BlobFile.md

@@ -0,0 +1,62 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / BlobFile
+
+# Class: BlobFile
+
+A lazy handle to blob bytes. Create one with [Table.fetchBlobFiles](Table.md#fetchblobfiles).
+
+## Methods
+
+### read()
+
+```ts
+read(): Promise<Buffer>
+```
+
+Reads from the cursor to the end and advances the cursor.
+
+A second call returns an empty buffer. [BlobFile.readRange](BlobFile.md#readrange) does
+not move the cursor.
+
+#### Returns
+
+`Promise`&lt;`Buffer`&gt;
+
+***
+
+### readRange()
+
+```ts
+readRange(start, end): Promise<Buffer>
+```
+
+Reads the half-open byte range `[start, end)`.
+
+Fails when `end` is past the blob size. Does not move the cursor.
+
+#### Parameters
+
+* **start**: `bigint`
+
+* **end**: `bigint`
+
+#### Returns
+
+`Promise`&lt;`Buffer`&gt;
+
+***
+
+### size()
+
+```ts
+size(): bigint
+```
+
+Returns the blob size in bytes.
+
+#### Returns
+
+`bigint`

docs/src/js/classes/Table.md

@@ -137,6 +137,20 @@ containing the new version number of the table after altering the columns.
 
 ***
 
+### blobColumns()
+
+```ts
+abstract blobColumns(): Promise<string[]>
+```
+
+Blob v2 columns, including nested dotted paths.
+
+#### Returns
+
+`Promise`&lt;`string`[]&gt;
+
+***
+
 ### branches()
 
 ```ts
@@ -499,6 +513,54 @@ Drop an index from the table.
 
 ***
 
+### fetchBlobFiles()
+
+```ts
+abstract fetchBlobFiles(column, rowIds): Promise<(null | BlobFile)[]>
+```
+
+Opens lazy blob handles for `column` at the given row IDs using the
+table's current checkout.
+
+Preserves input order, duplicates, and nulls. Use this for large payloads.
+See [Table.fetchBlobs](Table.md#fetchblobs) for row-ID validity across versions.
+
+#### Parameters
+
+* **column**: `string`
+
+* **rowIds**: readonly (`number` \| `bigint`)[]
+
+#### Returns
+
+`Promise`&lt;(`null` \| [`BlobFile`](BlobFile.md))[]&gt;
+
+***
+
+### fetchBlobs()
+
+```ts
+abstract fetchBlobs(column, rowIds): Promise<(null | Buffer)[]>
+```
+
+Bytes for `column` at row IDs from [Query.withRowId](Query.md#withrowid).
+
+Reads the table's current checkout. IDs from another version can fail after
+compaction unless stable row ids are enabled. Results keep input order and
+duplicates. Null blobs are `null`. Empty blobs are empty buffers.
+
+#### Parameters
+
+* **column**: `string`
+
+* **rowIds**: readonly (`number` \| `bigint`)[]
+
+#### Returns
+
+`Promise`&lt;(`null` \| `Buffer`)[]&gt;
+
+***
+
 ### flushLsm()
 
 ```ts

docs/src/js/functions/blob.md

@@ -0,0 +1,55 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / blob
+
+# Function: blob()
+
+```ts
+function blob(name, options): Field
+```
+
+Declares a `lance.blob.v2` column.
+
+Query results are descriptors, not payload bytes. Use [Table.fetchBlobs](../classes/Table.md#fetchblobs)
+or [Table.fetchBlobFiles](../classes/Table.md#fetchblobfiles) to read bytes.
+
+## Parameters
+
+* **name**: `string`
+
+* **options**: [`BlobOptions`](../type-aliases/BlobOptions.md) = `{}`
+
+## Returns
+
+`Field`
+
+## Example
+
+```ts
+import { readFile } from "node:fs/promises";
+import { Field, Int64, Schema } from "apache-arrow";
+import { blob, connect } from "@lancedb/lancedb";
+
+const db = await connect("./data");
+const video = await readFile("clip.mp4");
+const table = await db.createTable(
+  "videos",
+  [{ id: 1n, video }],
+  {
+    schema: new Schema([
+      new Field("id", new Int64()),
+      blob("video"),
+    ]),
+  },
+);
+
+const rows = await table.query().select(["id"]).withRowId().toArray();
+const rowIds = rows.map((row) => row._rowid as bigint);
+const bytes = await table.fetchBlobs("video", rowIds);
+
+const [handle] = await table.fetchBlobFiles("video", rowIds);
+const size = handle!.size();
+const header = await handle!.readRange(0n, size < 65536n ? size : 65536n);
+```

docs/src/js/functions/isBlobField.md

@@ -0,0 +1,22 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / isBlobField
+
+# Function: isBlobField()
+
+```ts
+function isBlobField(field): boolean
+```
+
+Checks for the `lance.blob.v2` extension marker. Does not validate the
+field's storage type.
+
+## Parameters
+
+* **field**: `Field`<`any`>
+
+## Returns
+
+`boolean`

docs/src/js/globals.md

@@ -19,6 +19,7 @@
 ## Classes
 
 - [AutoQuery](classes/AutoQuery.md)
+- [BlobFile](classes/BlobFile.md)
 - [BooleanQuery](classes/BooleanQuery.md)
 - [BoostQuery](classes/BoostQuery.md)
 - [BranchContents](classes/BranchContents.md)
@@ -143,6 +144,7 @@
 
 - [AnalyzePlanDistributedMetrics](type-aliases/AnalyzePlanDistributedMetrics.md)
 - [BaseTokenizer](type-aliases/BaseTokenizer.md)
+- [BlobOptions](type-aliases/BlobOptions.md)
 - [Data](type-aliases/Data.md)
 - [DataLike](type-aliases/DataLike.md)
 - [FieldLike](type-aliases/FieldLike.md)
@@ -158,9 +160,11 @@
 ## Functions
 
 - [RecordBatchIterator](functions/RecordBatchIterator.md)
+- [blob](functions/blob.md)
 - [connect](functions/connect.md)
 - [connectNamespace](functions/connectNamespace.md)
 - [instrumentLanceDbMetrics](functions/instrumentLanceDbMetrics.md)
+- [isBlobField](functions/isBlobField.md)
 - [makeArrowTable](functions/makeArrowTable.md)
 - [packBits](functions/packBits.md)
 - [permutationBuilder](functions/permutationBuilder.md)

docs/src/js/type-aliases/BlobOptions.md

@@ -0,0 +1,48 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / BlobOptions
+
+# Type Alias: BlobOptions
+
+```ts
+type BlobOptions: object;
+```
+
+## Type declaration
+
+### dedicatedSizeThreshold?
+
+```ts
+optional dedicatedSizeThreshold: number;
+```
+
+Max payload bytes stored in a packed sidecar before a dedicated file. Must
+be a positive safe integer.
+
+### inlineSizeThreshold?
+
+```ts
+optional inlineSizeThreshold: number;
+```
+
+Max payload bytes kept inline in the data file. Zero is allowed. Must be a
+safe integer.
+
+### nullable?
+
+```ts
+optional nullable: boolean;
+```
+
+Defaults to true.
+
+### packFileSizeThreshold?
+
+```ts
+optional packFileSizeThreshold: number;
+```
+
+Max bytes in one packed sidecar before starting another. Must be a positive
+safe integer.

java/pom.xml

@@ -28,7 +28,7 @@
     <properties>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
         <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>12.0.0-beta.15</lance-core.version>
+        <lance-core.version>12.0.0-beta.18</lance-core.version>
         <spotless.skip>false</spotless.skip>
         <spotless.version>2.30.0</spotless.version>
         <spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>

nodejs/__test__/blob.test.ts

@@ -0,0 +1,185 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import { Field, Int64, List, Schema, Struct, Utf8 } from "apache-arrow";
+import { makeArrowTable } from "../lancedb/arrow";
+import { BlobFile, blob, coerceBlobValue, isBlobField } from "../lancedb/blob";
+
+describe("blob()", () => {
+  it("marks the field as lance.blob.v2", () => {
+    const field = blob("image", { nullable: false });
+    expect(field.nullable).toBe(false);
+    expect(isBlobField(field)).toBe(true);
+    expect(field.metadata.get("ARROW:extension:name")).toBe("lance.blob.v2");
+  });
+
+  it("writes encoding thresholds as field metadata", () => {
+    const field = blob("video", {
+      inlineSizeThreshold: 1024,
+      dedicatedSizeThreshold: 2 * 1024 * 1024,
+      packFileSizeThreshold: 64 * 1024 * 1024,
+    });
+    expect(
+      field.metadata.get("lance-encoding:blob-inline-size-threshold"),
+    ).toBe("1024");
+    expect(
+      field.metadata.get("lance-encoding:blob-dedicated-size-threshold"),
+    ).toBe(String(2 * 1024 * 1024));
+    expect(
+      field.metadata.get("lance-encoding:blob-pack-file-size-threshold"),
+    ).toBe(String(64 * 1024 * 1024));
+  });
+
+  it("rejects invalid thresholds", () => {
+    expect(() => blob("image", { inlineSizeThreshold: -1 })).toThrow(
+      /inlineSizeThreshold must be non-negative/,
+    );
+    expect(() => blob("image", { dedicatedSizeThreshold: 0 })).toThrow(
+      /dedicatedSizeThreshold must be positive/,
+    );
+    expect(() => blob("image", { packFileSizeThreshold: 1.5 })).toThrow(
+      /packFileSizeThreshold must be a safe integer/,
+    );
+    expect(() =>
+      blob("image", { dedicatedSizeThreshold: Number.MAX_SAFE_INTEGER + 1 }),
+    ).toThrow(/dedicatedSizeThreshold must be a safe integer/);
+  });
+});
+
+describe("coerceBlobValue", () => {
+  it.each([
+    ["Buffer", Buffer.from("x"), { data: Buffer.from("x"), uri: null }],
+    [
+      "Uint8Array",
+      new Uint8Array([120]),
+      { data: new Uint8Array([120]), uri: null },
+    ],
+    ["URI string", "s3://bucket/key", { data: null, uri: "s3://bucket/key" }],
+    [
+      "data struct",
+      { data: Buffer.from("y") },
+      { data: Buffer.from("y"), uri: null },
+    ],
+    [
+      "uri struct",
+      { uri: "s3://bucket/key" },
+      { data: null, uri: "s3://bucket/key" },
+    ],
+    ["null", null, null],
+  ])("accepts %s", (_name, input, expected) => {
+    expect(coerceBlobValue(input)).toEqual(expected);
+  });
+
+  it.each([
+    ["empty URI", "", /uri cannot be empty/],
+    ["object without data or uri", { position: 0 }, /data' or 'uri/],
+    [
+      "Int16Array",
+      new Int16Array([1]),
+      /Blob data must be Buffer or Uint8Array/,
+    ],
+    [
+      "both data and uri",
+      { data: Buffer.from("y"), uri: "s3://bucket/key" },
+      /exactly one of 'data' or 'uri'/,
+    ],
+    [
+      "neither data nor uri",
+      { data: null, uri: null },
+      /exactly one of 'data' or 'uri'/,
+    ],
+  ])("rejects %s", (_name, input, message) => {
+    expect(() => coerceBlobValue(input)).toThrow(message);
+  });
+});
+
+describe("BlobFile", () => {
+  it("rejects constructing BlobFile without a native handle", () => {
+    expect(() => new (BlobFile as unknown as { new (): BlobFile })()).toThrow(
+      /fetchBlobFiles/,
+    );
+  });
+});
+
+describe("makeArrowTable blob columns", () => {
+  it("coerces Buffer input onto a blob field", () => {
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      blob("image"),
+    ]);
+    const table = makeArrowTable([{ id: 1n, image: Buffer.from("hello") }], {
+      schema,
+    });
+    expect(isBlobField(table.schema.fields[1])).toBe(true);
+    const image = table.getChild("image")!;
+    expect(image.nullCount).toBe(0);
+    expect(image.getChild("uri")!.get(0)).toBeNull();
+    expect(image.getChild("data")!.nullCount).toBe(0);
+    expect(Buffer.from(image.getChild("data")!.get(0)!).toString()).toBe(
+      "hello",
+    );
+  });
+
+  it("coerces Buffer elements inside a list and keeps null slots", () => {
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("images", new List(blob("image")), true),
+    ]);
+    const table = makeArrowTable(
+      [
+        { id: 1n, images: [Buffer.from("a"), Buffer.from("bb")] },
+        { id: 2n, images: null },
+        { id: 3n, images: [Buffer.from("c"), null] },
+        { id: 4n, images: [] },
+      ],
+      { schema },
+    );
+    const images = table.getChild("images")!;
+    expect(images.nullCount).toBe(1);
+    const rows = images.toArray();
+    expect(rows[1]).toBeNull();
+    expect(Array.from(rows[3] as Iterable<unknown>)).toHaveLength(0);
+    const first = Array.from(rows[0] as Iterable<{ data: Uint8Array | null }>);
+    expect(Buffer.from(first[0].data!).toString()).toBe("a");
+    expect(Buffer.from(first[1].data!).toString()).toBe("bb");
+    const third = Array.from(
+      rows[2] as Iterable<{ data: Uint8Array | null } | null>,
+    );
+    expect(Buffer.from(third[0]!.data!).toString()).toBe("c");
+    expect(third[1]).toBeNull();
+  });
+
+  it("coerces Buffer fields inside list structs", () => {
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "items",
+        new List(
+          new Field(
+            "item",
+            new Struct([new Field("name", new Utf8(), true), blob("image")]),
+            true,
+          ),
+        ),
+        true,
+      ),
+    ]);
+    const table = makeArrowTable(
+      [
+        {
+          id: 1n,
+          items: [{ name: "one", image: Buffer.from("alpha") }],
+        },
+      ],
+      { schema },
+    );
+    const items = Array.from(
+      table.getChild("items")!.toArray()[0] as Iterable<{
+        name: string;
+        image: { data: Uint8Array | null };
+      }>,
+    );
+    expect(items[0].name).toBe("one");
+    expect(Buffer.from(items[0].image.data!).toString()).toBe("alpha");
+  });
+});

nodejs/__test__/table.test.ts

@@ -18,6 +18,7 @@ import {
   Query,
   Table,
   VectorQuery,
+  blob,
   connect,
   tokenize,
 } from "../lancedb";
@@ -2401,6 +2402,276 @@ describe("when dealing with versioning", () => {
   });
 });
 
+describe("when dealing with blob columns", () => {
+  let tmpDir: tmp.DirResult;
+  beforeEach(() => {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  });
+  afterEach(() => {
+    tmpDir.removeCallback();
+  });
+
+  it("discovers blob columns", async () => {
+    const { table } = await openBlobTable();
+    expect(await table.blobColumns()).toEqual(["image"]);
+  });
+
+  it("preserves order, duplicates, and nulls", async () => {
+    const { table, rowIds } = await openBlobTable();
+    const [alphaId, betaId, nullId] = rowIds;
+    const bytes = await table.fetchBlobs("image", [
+      betaId,
+      alphaId,
+      betaId,
+      nullId,
+    ]);
+    expect(bytes.map((b) => (b == null ? null : b.toString()))).toEqual([
+      "beta",
+      "alpha",
+      "beta",
+      null,
+    ]);
+    const files = await table.fetchBlobFiles("image", [
+      betaId,
+      nullId,
+      alphaId,
+    ]);
+    expect(files.map((f) => f == null)).toEqual([false, true, false]);
+  });
+
+  it("reads full blob contents", async () => {
+    const { table, rowIds, alpha, beta } = await openBlobTable();
+    const bytes = await table.fetchBlobs("image", rowIds);
+    expect(bytes[0]!.equals(alpha)).toBe(true);
+    expect(bytes[1]!.equals(beta)).toBe(true);
+    const files = await table.fetchBlobFiles("image", rowIds);
+    expect(files[0]!.size()).toBe(BigInt(alpha.length));
+    expect(Buffer.from(await files[0]!.read()).toString()).toBe("alpha");
+    expect(Buffer.from(await files[1]!.read()).toString()).toBe("beta");
+  });
+
+  it("reads a half-open range", async () => {
+    const { table, rowIds } = await openBlobTable();
+    const files = await table.fetchBlobFiles("image", rowIds);
+    expect(Buffer.from(await files[0]!.readRange(0n, 2n)).toString()).toBe(
+      "al",
+    );
+  });
+
+  it("readRange does not move the cursor", async () => {
+    const { table, rowIds, alpha } = await openBlobTable();
+    const [handle] = await table.fetchBlobFiles("image", rowIds);
+    expect((await handle!.readRange(1n, 3n)).toString()).toBe("lp");
+    expect(await handle!.read()).toEqual(alpha);
+    expect(await handle!.read()).toEqual(Buffer.alloc(0));
+  });
+
+  it("fails when readRange end is past the blob size", async () => {
+    const { table, rowIds, alpha } = await openBlobTable();
+    const files = await table.fetchBlobFiles("image", rowIds);
+    await expect(
+      files[0]!.readRange(0n, BigInt(alpha.length + 1)),
+    ).rejects.toThrow(/exceeds blob size/);
+  });
+
+  it("rejects fetchBlobs on a non-blob column", async () => {
+    const { table, rowIds } = await openBlobTable();
+    await expect(table.fetchBlobs("id", rowIds)).rejects.toThrow(/blob/i);
+  });
+
+  it("discovers and fetches nested blob columns", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("info", new Struct([blob("image")]), true),
+    ]);
+    const payload = Buffer.from("nested");
+    const table = await db.createTable(
+      "nested_blobs",
+      [{ id: 1n, info: { image: payload } }],
+      { schema },
+    );
+    expect(await table.blobColumns()).toEqual(["info.image"]);
+    const rows = await table.query().withRowId().toArray();
+    const bytes = await table.fetchBlobs("info.image", [
+      rows[0]._rowid as bigint,
+    ]);
+    expect(bytes[0]!.equals(payload)).toBe(true);
+  });
+
+  it("creates and adds list blob columns", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("images", new List(blob("image")), true),
+    ]);
+    const alpha = Buffer.from("alpha");
+    const beta = Buffer.from("beta");
+    const gamma = Buffer.from("gamma");
+    const table = await db.createTable(
+      "list_blobs",
+      [{ id: 1n, images: [alpha, beta] }],
+      { schema },
+    );
+    await table.add([
+      { id: 2n, images: null },
+      { id: 3n, images: [gamma, null] },
+      { id: 4n, images: [] },
+    ]);
+    expect(await table.blobColumns()).toEqual(["images.image"]);
+    const rows = await table.query().toArray();
+    const byId = new Map(rows.map((row) => [Number(row.id), row]));
+    expect(descriptorSizes(byId.get(1)!.images)).toEqual([
+      alpha.length,
+      beta.length,
+    ]);
+    expect(byId.get(2)!.images).toBeNull();
+    expect(descriptorSizes(byId.get(3)!.images)).toEqual([gamma.length, null]);
+    expect(Array.from(byId.get(4)!.images as Iterable<unknown>)).toHaveLength(
+      0,
+    );
+  });
+
+  it("creates and adds list struct blob columns", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "items",
+        new List(
+          new Field(
+            "item",
+            new Struct([new Field("name", new Utf8(), true), blob("image")]),
+            true,
+          ),
+        ),
+        true,
+      ),
+    ]);
+    const alpha = Buffer.from("nested-alpha");
+    const beta = Buffer.from("nested-beta");
+    const table = await db.createTable(
+      "list_struct_blobs",
+      [{ id: 1n, items: [{ name: "one", image: alpha }] }],
+      { schema },
+    );
+    await table.add([
+      {
+        id: 2n,
+        items: [
+          { name: "two", image: beta },
+          { name: "three", image: null },
+        ],
+      },
+    ]);
+    const rows = await table.query().toArray();
+    const byId = new Map(rows.map((row) => [Number(row.id), row]));
+    expect(
+      descriptorSizes(
+        Array.from(byId.get(1)!.items as Iterable<{ image: unknown }>).map(
+          (item) => item.image,
+        ),
+      ),
+    ).toEqual([alpha.length]);
+    expect(
+      descriptorSizes(
+        Array.from(byId.get(2)!.items as Iterable<{ image: unknown }>).map(
+          (item) => item.image,
+        ),
+      ),
+    ).toEqual([beta.length, null]);
+  });
+
+  it("rejects blob fields inside a fixed-size list", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("frames", new FixedSizeList(2, blob("frame")), true),
+    ]);
+    await expect(
+      db.createTable(
+        "fsl_blobs",
+        [{ id: 1n, frames: [Buffer.from("a"), Buffer.from("b")] }],
+        { schema },
+      ),
+    ).rejects.toThrow(
+      "Blob fields inside FixedSizeList are not supported. Use List instead.",
+    );
+  });
+
+  it("rejects blob fields inside a nested fixed-size list", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "clip",
+        new Struct([
+          new Field("frames", new FixedSizeList(2, blob("frame")), true),
+        ]),
+        true,
+      ),
+    ]);
+    await expect(
+      db.createTable(
+        "nested_fsl_blobs",
+        [
+          {
+            id: 1n,
+            clip: { frames: [Buffer.from("a"), Buffer.from("b")] },
+          },
+        ],
+        { schema },
+      ),
+    ).rejects.toThrow(
+      "Blob fields inside FixedSizeList are not supported. Use List instead.",
+    );
+  });
+
+  it("rejects an Arrow table with blob fields inside a fixed-size list", async () => {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field("frames", new FixedSizeList(2, blob("frame")), true),
+    ]);
+    await expect(
+      db.createTable("fsl_blobs_ipc", new ArrowTable(schema)),
+    ).rejects.toThrow(
+      "Blob fields inside FixedSizeList are not supported. Use List instead.",
+    );
+  });
+
+  function descriptorSizes(values: unknown): (number | null)[] {
+    return Array.from(
+      values as Iterable<{ size?: bigint | number } | null>,
+    ).map((value) => (value == null ? null : Number(value.size)));
+  }
+
+  async function openBlobTable() {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      blob("image"),
+    ]);
+    const alpha = Buffer.from("alpha");
+    const beta = Buffer.from("beta");
+    const table = await db.createTable(
+      "blobs",
+      [
+        { id: 1n, image: alpha },
+        { id: 2n, image: beta },
+        { id: 3n, image: null },
+      ],
+      { schema },
+    );
+    const rows = await table.query().withRowId().toArray();
+    const rowIdById = new Map(
+      rows.map((r) => [Number(r.id), r._rowid as bigint]),
+    );
+    const rowIds = [1, 2, 3].map((id) => rowIdById.get(id)!);
+    return { table, rowIds, alpha, beta };
+  }
+});
+
 describe("when dealing with tags", () => {
   let tmpDir: tmp.DirResult;
   beforeEach(() => {

nodejs/lancedb/arrow.ts

@@ -40,6 +40,7 @@ import {
 } from "apache-arrow";
 import { Buffers } from "apache-arrow/data";
 import { typedArrayToArrowType } from "./arrow_type";
+import { coerceBlobValue, isBlobField } from "./blob";
 import { type EmbeddingFunction } from "./embedding/embedding_function";
 import {
   EmbeddingFunctionConfig,
@@ -430,12 +431,14 @@ export function makeArrowTable(
       throw new Error("A schema must be provided if data is empty");
     } else {
       schema = new Schema(schema.fields, schemaMetadata);
+      validateBlobSchema(schema);
       return new ArrowTable(schema);
     }
   }
 
   let inferredSchema = inferSchema(data, schema, opt);
   inferredSchema = new Schema(inferredSchema.fields, schemaMetadata);
+  validateBlobSchema(inferredSchema);
 
   const finalColumns: Record<string, Vector> = {};
   for (const field of inferredSchema.fields) {
@@ -445,6 +448,35 @@ export function makeArrowTable(
   return new ArrowTable(inferredSchema, finalColumns);
 }
 
+function validateBlobSchema(schema: Schema): void {
+  for (const field of schema.fields) {
+    validateBlobField(field);
+  }
+}
+
+function validateBlobField(field: Field): void {
+  if (
+    isFixedSizeList(field.type) &&
+    containsBlobField(field.type.children[0])
+  ) {
+    throw new Error(
+      "Blob fields inside FixedSizeList are not supported. Use List instead.",
+    );
+  }
+  for (const child of field.type.children ?? []) {
+    validateBlobField(child);
+  }
+}
+
+function containsBlobField(field: Field): boolean {
+  if (isBlobField(field)) {
+    return true;
+  }
+  return (field.type.children ?? []).some((child: Field) =>
+    containsBlobField(child),
+  );
+}
+
 function isObject(value: unknown): value is Record<string, unknown> {
   return (
     typeof value === "object" &&
@@ -480,6 +512,32 @@ function transposeData(
   path: string[] = [],
 ): Vector {
   const valuesPath = [...path, field.name];
+  if (isBlobField(field) && field.type instanceof Struct) {
+    const blobRows = data.map((datum) =>
+      coerceBlobValue(valueAtPath(datum, valuesPath)),
+    );
+    const childVectors = field.type.children.map((child) => {
+      const values = blobRows.map((row) =>
+        row == null ? null : (row[child.name as "data" | "uri"] ?? null),
+      );
+      return makeVector(values, child.type, undefined, child.nullable);
+    });
+    const nullCount = blobRows.filter((row) => row === null).length;
+    const structData = makeData({
+      type: field.type,
+      length: blobRows.length,
+      nullCount,
+      nullBitmap:
+        nullCount > 0
+          ? arrowUtil.packBools(blobRows.map((row) => row !== null))
+          : undefined,
+      children: childVectors.map((v) => v.data[0]),
+    });
+    return arrowMakeVector(structData);
+  }
+  if (isList(field.type) && containsBlobField(field.type.children[0])) {
+    return transposeListData(data, field, valuesPath);
+  }
   const values = data.map((datum) => valueAtPath(datum, valuesPath));
   if (field.type instanceof Struct) {
     const childFields = field.type.children;
@@ -495,7 +553,7 @@ function transposeData(
         nullCount > 0
           ? arrowUtil.packBools(values.map((value) => value !== null))
           : undefined,
-      children: childVectors as unknown as ArrowData<DataType>[],
+      children: childVectors.map((v) => v.data[0]),
     });
     return arrowMakeVector(structData);
   } else {
@@ -503,6 +561,48 @@ function transposeData(
   }
 }
 
+function transposeListData(
+  data: Record<string, unknown>[],
+  field: Field,
+  valuesPath: string[],
+): Vector {
+  const listType = field.type as List;
+  const childField = listType.children[0];
+  const lists = data.map((datum) => valueAtPath(datum, valuesPath));
+  const flattened: Record<string, unknown>[] = [];
+  const validity: boolean[] = [];
+  const offsets: number[] = [0];
+
+  for (const list of lists) {
+    if (list == null) {
+      validity.push(false);
+      offsets.push(flattened.length);
+      continue;
+    }
+    if (!Array.isArray(list)) {
+      throw new Error(`expected an array for list field '${field.name}'`);
+    }
+    validity.push(true);
+    for (const element of list) {
+      flattened.push({ [childField.name]: element });
+    }
+    offsets.push(flattened.length);
+  }
+
+  const childVector = transposeData(flattened, childField, []);
+  const nullCount = validity.filter((valid) => !valid).length;
+  return arrowMakeVector(
+    makeData({
+      type: listType,
+      length: lists.length,
+      nullCount,
+      nullBitmap: nullCount > 0 ? arrowUtil.packBools(validity) : undefined,
+      valueOffsets: Int32Array.from(offsets),
+      child: childVector.data[0],
+    }),
+  );
+}
+
 /**
  * Create an empty Arrow table with the provided schema
  */
@@ -952,6 +1052,7 @@ export async function fromTableToBuffer(
     schema = sanitizeSchema(schema);
   }
   const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
+  validateBlobSchema(tableWithEmbeddings.schema);
   const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings);
   return Buffer.from(await writer.toUint8Array());
 }

nodejs/lancedb/blob.ts

@@ -0,0 +1,236 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import { Field, LargeBinary, Struct, Utf8 } from "apache-arrow";
+import { BlobFile as NativeBlobFile } from "./native";
+
+const BLOB_V2_EXTENSION_NAME = "lance.blob.v2";
+
+const INLINE_SIZE_THRESHOLD_KEY = "lance-encoding:blob-inline-size-threshold";
+const DEDICATED_SIZE_THRESHOLD_KEY =
+  "lance-encoding:blob-dedicated-size-threshold";
+const PACK_FILE_SIZE_THRESHOLD_KEY =
+  "lance-encoding:blob-pack-file-size-threshold";
+
+export type BlobInput = {
+  data: Buffer | Uint8Array | null;
+  uri: string | null;
+};
+
+export type BlobOptions = {
+  /** Defaults to true. */
+  nullable?: boolean;
+  /**
+   * Max payload bytes kept inline in the data file. Zero is allowed. Must be a
+   * safe integer.
+   */
+  inlineSizeThreshold?: number;
+  /**
+   * Max payload bytes stored in a packed sidecar before a dedicated file. Must
+   * be a positive safe integer.
+   */
+  dedicatedSizeThreshold?: number;
+  /**
+   * Max bytes in one packed sidecar before starting another. Must be a positive
+   * safe integer.
+   */
+  packFileSizeThreshold?: number;
+};
+
+/**
+ * Declares a `lance.blob.v2` column.
+ *
+ * Query results are descriptors, not payload bytes. Use {@link Table.fetchBlobs}
+ * or {@link Table.fetchBlobFiles} to read bytes.
+ *
+ * @example
+ * ```ts
+ * import { readFile } from "node:fs/promises";
+ * import { Field, Int64, Schema } from "apache-arrow";
+ * import { blob, connect } from "@lancedb/lancedb";
+ *
+ * const db = await connect("./data");
+ * const video = await readFile("clip.mp4");
+ * const table = await db.createTable(
+ *   "videos",
+ *   [{ id: 1n, video }],
+ *   {
+ *     schema: new Schema([
+ *       new Field("id", new Int64()),
+ *       blob("video"),
+ *     ]),
+ *   },
+ * );
+ *
+ * const rows = await table.query().select(["id"]).withRowId().toArray();
+ * const rowIds = rows.map((row) => row._rowid as bigint);
+ * const bytes = await table.fetchBlobs("video", rowIds);
+ *
+ * const [handle] = await table.fetchBlobFiles("video", rowIds);
+ * const size = handle!.size();
+ * const header = await handle!.readRange(0n, size < 65536n ? size : 65536n);
+ * ```
+ */
+export function blob(name: string, options: BlobOptions = {}): Field {
+  const metadata = new Map<string, string>([
+    ["ARROW:extension:name", BLOB_V2_EXTENSION_NAME],
+  ]);
+  setThreshold(
+    metadata,
+    INLINE_SIZE_THRESHOLD_KEY,
+    "inlineSizeThreshold",
+    options.inlineSizeThreshold,
+    0,
+  );
+  setThreshold(
+    metadata,
+    DEDICATED_SIZE_THRESHOLD_KEY,
+    "dedicatedSizeThreshold",
+    options.dedicatedSizeThreshold,
+    1,
+  );
+  setThreshold(
+    metadata,
+    PACK_FILE_SIZE_THRESHOLD_KEY,
+    "packFileSizeThreshold",
+    options.packFileSizeThreshold,
+    1,
+  );
+  return new Field(
+    name,
+    new Struct([
+      new Field("data", new LargeBinary(), true),
+      new Field("uri", new Utf8(), true),
+    ]),
+    options.nullable ?? true,
+    metadata,
+  );
+}
+
+/**
+ * Checks for the `lance.blob.v2` extension marker. Does not validate the
+ * field's storage type.
+ */
+export function isBlobField(field: Field): boolean {
+  return field.metadata?.get("ARROW:extension:name") === BLOB_V2_EXTENSION_NAME;
+}
+
+/**
+ * A lazy handle to blob bytes. Create one with {@link Table.fetchBlobFiles}.
+ *
+ * @hideconstructor
+ */
+export class BlobFile {
+  private readonly inner: NativeBlobFile;
+
+  private constructor(inner: NativeBlobFile) {
+    if (!(inner instanceof NativeBlobFile)) {
+      throw new Error("BlobFile handles come from Table.fetchBlobFiles");
+    }
+    this.inner = inner;
+  }
+
+  /** @ignore */
+  static fromNative(inner: NativeBlobFile): BlobFile {
+    return new BlobFile(inner);
+  }
+
+  /** Returns the blob size in bytes. */
+  size(): bigint {
+    return this.inner.size();
+  }
+
+  /**
+   * Reads from the cursor to the end and advances the cursor.
+   *
+   * A second call returns an empty buffer. {@link BlobFile.readRange} does
+   * not move the cursor.
+   */
+  read(): Promise<Buffer> {
+    return this.inner.read();
+  }
+
+  /**
+   * Reads the half-open byte range `[start, end)`.
+   *
+   * Fails when `end` is past the blob size. Does not move the cursor.
+   */
+  readRange(start: bigint, end: bigint): Promise<Buffer> {
+    return this.inner.readRange(start, end);
+  }
+}
+
+export function coerceBlobValue(value: unknown): BlobInput | null {
+  if (value == null) {
+    return null;
+  }
+  if (isBlobBytes(value)) {
+    return { data: value, uri: null };
+  }
+  if (ArrayBuffer.isView(value)) {
+    throw new Error("Blob data must be Buffer or Uint8Array");
+  }
+  if (typeof value === "string") {
+    if (value === "") {
+      throw new Error("Blob uri cannot be empty");
+    }
+    return { data: null, uri: value };
+  }
+  if (typeof value === "object") {
+    const record = value as Record<string, unknown>;
+    if (!("data" in record) && !("uri" in record)) {
+      throw new Error(
+        "Blob struct values must include a 'data' or 'uri' field",
+      );
+    }
+    const uri = record.uri;
+    if (uri === "") {
+      throw new Error("Blob uri cannot be empty");
+    }
+    if (uri != null && typeof uri !== "string") {
+      throw new Error(`Blob uri must be a string or null, got ${typeof uri}`);
+    }
+    const data = record.data;
+    if (data != null && !isBlobBytes(data)) {
+      throw new Error("Blob data must be Buffer, Uint8Array, or null");
+    }
+    const bytes = (data as Buffer | Uint8Array | null | undefined) ?? null;
+    const uriValue = uri ?? null;
+    if ((bytes == null) === (uriValue == null)) {
+      throw new Error(
+        "Blob struct values must set exactly one of 'data' or 'uri'",
+      );
+    }
+    return { data: bytes, uri: uriValue };
+  }
+  throw new Error(
+    "Blob column values must be Buffer, Uint8Array, a URI string, null, or { data?, uri? }",
+  );
+}
+
+function isBlobBytes(value: unknown): value is Buffer | Uint8Array {
+  return Buffer.isBuffer(value) || value instanceof Uint8Array;
+}
+
+function setThreshold(
+  metadata: Map<string, string>,
+  key: string,
+  optionName: string,
+  value: number | undefined,
+  minimum: number,
+): void {
+  if (value === undefined) {
+    return;
+  }
+  if (!Number.isSafeInteger(value)) {
+    throw new Error(`${optionName} must be a safe integer`);
+  }
+  if (value < minimum) {
+    throw new Error(
+      minimum <= 0
+        ? `${optionName} must be non-negative`
+        : `${optionName} must be positive`,
+    );
+  }
+  metadata.set(key, String(value));
+}

nodejs/lancedb/index.ts

@@ -77,6 +77,9 @@ export {
   VectorColumnOptions,
 } from "./arrow";
 
+export { blob, isBlobField, BlobFile } from "./blob";
+export type { BlobOptions } from "./blob";
+
 export {
   Connection,
   CreateTableOptions,

nodejs/lancedb/table.ts

@@ -17,6 +17,7 @@ import {
   tableFromIPC,
 } from "./arrow";
 
+import { BlobFile } from "./blob";
 import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
 import { IndexOptions } from "./indices";
 import { Job } from "./job";
@@ -510,6 +511,35 @@ export abstract class Table {
    */
   abstract takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery;
 
+  /**
+   * Blob v2 columns, including nested dotted paths.
+   */
+  abstract blobColumns(): Promise<string[]>;
+
+  /**
+   * Bytes for `column` at row IDs from {@link Query.withRowId}.
+   *
+   * Reads the table's current checkout. IDs from another version can fail after
+   * compaction unless stable row ids are enabled. Results keep input order and
+   * duplicates. Null blobs are `null`. Empty blobs are empty buffers.
+   */
+  abstract fetchBlobs(
+    column: string,
+    rowIds: readonly (bigint | number)[],
+  ): Promise<(Buffer | null)[]>;
+
+  /**
+   * Opens lazy blob handles for `column` at the given row IDs using the
+   * table's current checkout.
+   *
+   * Preserves input order, duplicates, and nulls. Use this for large payloads.
+   * See {@link Table.fetchBlobs} for row-ID validity across versions.
+   */
+  abstract fetchBlobFiles(
+    column: string,
+    rowIds: readonly (bigint | number)[],
+  ): Promise<(BlobFile | null)[]>;
+
   /**
    * Create a search query to find the nearest neighbors
    * of the given query
@@ -1160,23 +1190,34 @@ export class LocalTable extends Table {
   }
 
   takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery {
-    const ids = rowIds.map((id) => {
-      if (typeof id === "bigint") {
-        return id;
-      }
-      if (!Number.isInteger(id)) {
-        throw new Error("Row id must be an integer (or bigint)");
-      }
-      if (id < 0) {
-        throw new Error("Row id cannot be negative");
-      }
-      if (!Number.isSafeInteger(id)) {
-        throw new Error("Row id is too large for number; use bigint instead");
-      }
-      return BigInt(id);
-    });
+    return new TakeQuery(this.inner.takeRowIds(rowIdsToBigInts(rowIds)));
+  }
 
-    return new TakeQuery(this.inner.takeRowIds(ids));
+  blobColumns(): Promise<string[]> {
+    return this.inner.blobColumns();
+  }
+
+  async fetchBlobs(
+    column: string,
+    rowIds: readonly (bigint | number)[],
+  ): Promise<(Buffer | null)[]> {
+    const values = await this.inner.fetchBlobs(column, rowIdsToBigInts(rowIds));
+    // N-API Option maps missing values to undefined. Collapse those to null.
+    return values.map((value) => value ?? null);
+  }
+
+  async fetchBlobFiles(
+    column: string,
+    rowIds: readonly (bigint | number)[],
+  ): Promise<(BlobFile | null)[]> {
+    const files = await this.inner.fetchBlobFiles(
+      column,
+      rowIdsToBigInts(rowIds),
+    );
+    // N-API Option maps missing values to undefined. Collapse those to null.
+    return files.map((file) =>
+      file == null ? null : BlobFile.fromNative(file),
+    );
   }
 
   query(): Query {
@@ -1733,3 +1774,21 @@ export class Branches {
     )) as unknown as CherryPickResult;
   }
 }
+
+function rowIdsToBigInts(rowIds: readonly (bigint | number)[]): bigint[] {
+  return rowIds.map((id) => {
+    if (typeof id === "bigint") {
+      return id;
+    }
+    if (!Number.isInteger(id)) {
+      throw new Error("Row id must be an integer (or bigint)");
+    }
+    if (id < 0) {
+      throw new Error("Row id cannot be negative");
+    }
+    if (!Number.isSafeInteger(id)) {
+      throw new Error("Row id is too large for number; use bigint instead");
+    }
+    return BigInt(id);
+  });
+}

nodejs/src/blob.rs

@@ -0,0 +1,95 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+use std::ops::Range;
+use std::sync::Arc;
+
+use arrow_array::{Array, LargeBinaryArray};
+use lancedb::blob::BlobFile as LanceBlobFile;
+use napi::bindgen_prelude::*;
+use napi_derive::napi;
+
+use crate::error::convert_error;
+
+#[napi]
+pub struct BlobFile {
+    inner: Arc<LanceBlobFile>,
+}
+
+impl BlobFile {
+    pub(crate) fn new(inner: LanceBlobFile) -> Self {
+        Self {
+            inner: Arc::new(inner),
+        }
+    }
+}
+
+#[napi]
+impl BlobFile {
+    #[napi]
+    pub fn size(&self) -> BigInt {
+        BigInt::from(self.inner.size())
+    }
+
+    #[napi]
+    pub async fn read(&self) -> napi::Result<Buffer> {
+        let bytes = self.inner.read().await.map_err(|err| convert_error(&err))?;
+        Ok(Buffer::from(bytes.as_ref()))
+    }
+
+    #[napi]
+    pub async fn read_range(&self, start: BigInt, end: BigInt) -> napi::Result<Buffer> {
+        let range = bigint_range(start, end)?;
+        let bytes = self
+            .inner
+            .read_range(range)
+            .await
+            .map_err(|err| convert_error(&err))?;
+        Ok(Buffer::from(bytes.as_ref()))
+    }
+}
+
+fn bigint_range(start: BigInt, end: BigInt) -> napi::Result<Range<u64>> {
+    let start = parse_u64(start, "start")?;
+    let end = parse_u64(end, "end")?;
+    if start > end {
+        return Err(napi::Error::from_reason(format!(
+            "invalid blob range: start ({start}) > end ({end})"
+        )));
+    }
+    Ok(start..end)
+}
+
+fn parse_u64(value: BigInt, name: &str) -> napi::Result<u64> {
+    let (negative, value, lossless) = value.get_u64();
+    if negative {
+        return Err(napi::Error::from_reason(format!(
+            "{name} cannot be negative"
+        )));
+    }
+    if !lossless {
+        return Err(napi::Error::from_reason(format!(
+            "{name} is too large to fit in u64"
+        )));
+    }
+    Ok(value)
+}
+
+pub fn parse_row_ids(row_ids: Vec<BigInt>) -> napi::Result<Vec<u64>> {
+    row_ids
+        .into_iter()
+        .map(|id| parse_u64(id, "row id"))
+        .collect()
+}
+
+pub fn copy_blob_buffers(array: LargeBinaryArray) -> Vec<Option<Buffer>> {
+    (0..array.len())
+        .map(|i| {
+            if array.is_null(i) {
+                None
+            } else {
+                Some(Buffer::from(array.value(i).to_vec()))
+            }
+        })
+        .collect()
+}

nodejs/src/lib.rs

@@ -10,6 +10,7 @@ use std::collections::HashMap;
 use env_logger::Env;
 use napi_derive::*;
 
+mod blob;
 mod connection;
 mod error;
 mod header;

nodejs/src/table.rs

@@ -15,6 +15,7 @@ use napi::bindgen_prelude::*;
 use napi::threadsafe_function::{ThreadsafeFunction, ThreadsafeFunctionCallMode};
 use napi_derive::napi;
 
+use crate::blob::{BlobFile, copy_blob_buffers, parse_row_ids};
 use crate::error::NapiErrorExt;
 use crate::index::Index;
 use crate::merge::NativeMergeInsertBuilder;
@@ -329,6 +330,44 @@ impl Table {
         ))
     }
 
+    #[napi(catch_unwind)]
+    pub async fn blob_columns(&self) -> napi::Result<Vec<String>> {
+        self.inner_ref()?.blob_columns().await.default_error()
+    }
+
+    #[napi(catch_unwind)]
+    pub async fn fetch_blobs(
+        &self,
+        column: String,
+        row_ids: Vec<BigInt>,
+    ) -> napi::Result<Vec<Option<Buffer>>> {
+        let row_ids = parse_row_ids(row_ids)?;
+        let array = self
+            .inner_ref()?
+            .fetch_blobs(column.as_str(), &row_ids)
+            .await
+            .default_error()?;
+        Ok(copy_blob_buffers(array))
+    }
+
+    #[napi(catch_unwind)]
+    pub async fn fetch_blob_files(
+        &self,
+        column: String,
+        row_ids: Vec<BigInt>,
+    ) -> napi::Result<Vec<Option<BlobFile>>> {
+        let row_ids = parse_row_ids(row_ids)?;
+        let files = self
+            .inner_ref()?
+            .fetch_blob_files(column.as_str(), &row_ids)
+            .await
+            .default_error()?;
+        Ok(files
+            .into_iter()
+            .map(|file| file.map(BlobFile::new))
+            .collect())
+    }
+
     #[napi(catch_unwind)]
     pub fn vector_search(&self, vector: Float32Array) -> napi::Result<VectorQuery> {
         self.query()?.nearest_to(vector)