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Yang Cen
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Update the Rust workspace, Java dependency, and Python test dependency to [Lance v15.0.0-beta.17](https://github.com/lance-format/lance/releases/tag/v15.0.0-beta.17). This includes the FRI cache and vector-index changes required by current Sophon and retains the RaBitQ prewarm fixes. Lockfiles use the published source and test wheels without unrelated registry version bumps. The dependency dry run also exposed CI resource limits. Use the existing larger x64 runner for GNU Node and compatibility-wheel builds; allow 60 minutes for Mac Python tests, 120 minutes for the compatibility wheel, and 150 minutes for the Mac release wheel. Disable the CLI toolchain action's automatic target cache so only the subsequent downloads-only cache runs. Release optimization, the compatibility wheel's manylinux container and x86-64-v2 baseline, and test coverage stay unchanged. Validation: - Three native SDK regressions pass: refined RQ queries after deferred compaction, deferred index remapping, and ANN approximation planning. - Pinned Rust 1.97.0: `cargo clippy --quiet --locked --features remote --tests --examples -- -D warnings` passes. - Locked offline Rust metadata, Python lock validation, Ruff lint/format, and diff checks pass. The Python lock contains six published beta.17 wheels. - Repository YAML, whitespace and typo checks pass for the workflow changes. Product-source checks are reused for the subsequent CI-only commits. - At head `07033dc6`, all 65 applicable pre-review CI checks pass, including the compatibility wheel, Mac CLI, GNU Node, Mac Python tests, release wheels, and Java checks. Six checks are skipped by tag/main-only conditions or draft-only app behavior; the automated review and security checks run after the Ready transition. The upstream Java publisher succeeded and its beta.17 Maven artifact is available. Six upstream Python wheel builds/uploads succeeded; its Windows ARM job was cancelled. These checks do not establish Sophon performance or aggregate-memory acceptance.
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
Stay in Touch With Us