Dan RammerandClaude Opus 5
0ed17a653b
Targets `release/v0.39`, not `main`. That branch was cut from `56bbd19f`, the last commit on `main` still pinned to lance 12, and carries eight backported fixes; it will publish the next stable lancedb on the lance 12.0.0 release. ## What changed Rust workspace lance crates and `java/pom.xml` `lance-core` move from `v12.0.0-beta.18` to [`v12.0.0`](https://github.com/lance-format/lance/releases/tag/v12.0.0). No compatibility fixes were needed. Because the target is a stable lance, `ci/set_lance_version.py` takes the `set_stable_version` path, so the workspace dependencies drop their `git` and `tag` fields and resolve from crates.io. That switch is required for the release itself — `cargo publish` rejects a crate with git dependencies — and `Cargo.lock` now has zero `lance-format/lance` references. ## Validation * `python3 ci/validate_stable_lance.py` passes — the gate the `Create Release Commit` workflow runs for a stable release. * `cargo fmt --all`, `git diff --check` clean. * All lance 12.0.0 crates confirmed published on crates.io, and `org.lance:lance-core:12.0.0` on Maven Central. * Full build and test verification is delegated to this PR's CI, which also exercises the eight backported fixes on the branch. 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 5 (1M context) <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
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⭐ 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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