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Builds on #4359 (which added the Arrow 19-21 test aliases) and makes the package genuinely work across the whole peer range: * Resolve the library's own `apache-arrow` to 21.2.0 (devDependency) so the main CI jobs build, type-check and test on the newest release, and widen the peer range to `>=15.0.0 <22.0.0` instead of an exact pin. * Add a CI job that re-installs with `apache-arrow` resolved to 19.0.1 and 20.0.0 and runs the suite, covering what a consumer on those versions gets. * Arrow 21 overrides `Symbol.hasInstance` on Schema/Field/Table/RecordBatch/ Data so `instanceof` matches objects from another copy of the library, but not on DataType. The sanitizer's short-circuits therefore returned foreign schemas unchanged and Arrow's builders then failed with "Unrecognized type 'NONE'". Check the real prototype chain instead. * Sanitize the types added in Arrow 20/21 (LargeList, Utf8View, BinaryView, IntervalMonthDayNano), looked up dynamically so the library still compiles and runs on older Arrow releases, with a clear error when the installed Arrow lacks the type. Carry `variadicBuffers` through `Data`. * Loosen `FieldLike` so a branded DataType from another Arrow copy still type-checks; export the new `DataTypeLike`. * Share the Arrow version list between test files, exercise embedding function types per version in the registry tests, and add sanitize and end-to-end coverage for the new column types. * Enable `skipLibCheck`: flatbuffers 25 (via Arrow 21) ships declarations that need TypeScript 5.7+. * Record the new dev dependencies in the third-party license inventory. Co-Authored-By: Vincent Koc <vincentkoc@ieee.org> Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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.
Contributors
Stay in Touch With Us