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### Summary Closes #3363 Adds the four namespace management methods to the NodeJS `Connection`, bringing parity with the Rust core and Python bindings: - `listNamespaces(parent?, options?)` - `createNamespace(namespacePath, options?)` - `dropNamespace(namespacePath, options?)` - `describeNamespace(namespacePath)` ### Test plan - npm test - Ran a smoke test script ```typescript import { connect } from '<lancePath>' import { tmpdir } from "os"; import { mkdtempSync } from "fs"; import { join } from "path"; const dir = mkdtempSync(join(tmpdir(), "lancedb-smoke-")); console.log(`Using temp dir: ${dir}\n`); const db = await connect(dir, { namespaceClientProperties: { manifest_enabled: "true" }, }); console.log("Creating namespaces..."); await db.createNamespace(["analytics"]); await db.createNamespace(["analytics", "sales"], { properties: { owner: "brendan", purpose: "smoke-test" }, }); await db.createNamespace(["marketing"]); const root = await db.listNamespaces(); console.log("Root namespaces:", root.namespaces); const children = await db.listNamespaces(["analytics"]); console.log("Children of 'analytics':", children.namespaces); const descWithProps = await db.describeNamespace(["analytics", "sales"]); console.log("Describe analytics/sales (with properties):", descWithProps); const descNoProps = await db.describeNamespace(["analytics"]); console.log("Describe analytics (no properties):", descNoProps); console.log("Describing a non-existent namespace (expect error)..."); try { await db.describeNamespace(["does-not-exist"]); console.error(" UNEXPECTED: describe succeeded for non-existent namespace"); } catch (err) { console.log(` ✓ Got expected error: ${err.message.split("\n")[0]}`); } await db.dropNamespace(["marketing"]); const afterDrop = await db.listNamespaces(); console.log("Root after dropping marketing:", afterDrop.namespaces); await db.close(); console.log("\nAll operations completed successfully."); ``` ``` Using temp dir: /var/folders/bj/hn6jv9c50y301d1nx0y8xmn00000gn/T/lancedb-smoke-MUC5NI Creating namespaces... Root namespaces: [ 'analytics', 'marketing' ] Children of 'analytics': [ 'sales' ] Describe analytics/sales (with properties): { properties: { purpose: 'smoke-test', owner: 'brendan' } } Describe analytics (no properties): {} Describing a non-existent namespace (expect error)... ✓ Got expected error: lance error: Namespace error: Namespace not found: does-not-exist, rust/lance-namespace-impls/src/dir/manifest.rs:2495:14 Caused by: Namespace error: Namespace not found: does-not-exist, rust/lance-namespace-impls/src/dir/manifest.rs:2495:14 Caused by: Namespace not found: does-not-exist Root after dropping marketing: [ 'analytics' ] All operations completed successfully. ``` ### Documentation - regenerated docs
The Multimodal AI Lakehouse
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors
The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
Demo: Multimodal Search by Keyword, Vector or with SQL
Star LanceDB to get updates!
⭐ Click here ⭐ to see how fast we're growing!
Key Features:
- Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
- Comprehensive Search: Support for vector similarity search, full-text search and SQL.
- Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
- Advanced Features: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
Products:
- Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
- Cloud and Enterprise: Production-scale vector search with no servers to manage. Complete data sovereignty and security.
Ecosystem:
- Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
- Seamless Integration: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
- Rich Ecosystem: Integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
How to Install:
Follow the Quickstart doc to set up LanceDB locally.
API & SDK: We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|---|---|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/rest |
Join Us and Contribute
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.
Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.
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