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Yang Cen
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Upgrade the Rust Lance dependency, Java lance-core, and Python test dependency from beta.17 to the officially published [v15.0.0-beta.18](https://github.com/lance-format/lance/releases/tag/v15.0.0-beta.18) (`079fd77683a7acf056b0912f6ecda938e39ee120`). This provides a compatible SDK for the newer Lance source already adopted downstream. Rust registry versions and checksums are unchanged; the Python lock uses the six published beta.18 wheels. ### Compatibility The adopted release includes [Lance #10863](https://github.com/lance-format/lance/pull/10863): `FilteredReadOptionsProto.has_fragment_ids` distinguishes an explicit empty fragment selection. Older executors ignore this field, so upgrade executors before relying on the corrected empty-selection behavior. Rust callers constructing this generated struct need the new field. [Lance #10112](https://github.com/lance-format/lance/pull/10112) also replaces the internal `hamming_distance_batch` API with `hamming_distance_batch_into`. The Linux Python matrix timeout is raised from 30 to 60 minutes: the Python 3.13 cold native build and both test passes completed, but the job hit its limit during cleanup. Build profiles, test commands, and coverage are unchanged. ### Validation - Three native FRI/ANN regressions passed: deferred-compaction refined RQ, deferred index remapping, and approximate-query builder. - `cargo clippy --quiet --locked --features remote --tests --examples -- -D warnings` passed with pinned Rust 1.97.0. - Locked metadata, formatting, Python Makefile-scope Ruff checks, and `uv lock --check --offline` passed. - YAML, whitespace, end-of-file, and typo checks passed for the timeout-only workflow change. ### Publication and CI Java beta.18 is now published. After [Lance #10968](https://github.com/lance-format/lance/pull/10968) merged, the [normal publication workflow](https://github.com/lance-format/lance/actions/runs/43146352505) built all three JNI targets and published successfully; the Maven jar is available. The upstream Python publication run was cancelled after its Windows ARM job hit the one-hour timeout; six other wheels were published and are the actual artifacts recorded in this lock. Cross-platform SDK CI is still required. No performance claim is made by this dependency update.
The Multimodal Lakehouse for AI
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:
- LanceDB Embedded (open source): 100% open source, runs in your application's process; your data can live on local disk or in object storage. No vendor lock-in.
- LanceDB Enterprise: Production-scale distributed search, indexing, and maintenance. Plus, 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
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