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Downstream workspaces adopting Lance 15.0.0-beta.11 currently also resolve beta.10 because the SDK pins every Lance crate exactly. This produces incompatible Lance types across the SDK and the consumer. Update the workspace pins and lockfile to the published [v15.0.0-beta.11](https://github.com/lance-format/lance/releases/tag/v15.0.0-beta.11). This release includes payload-free list length reads and preserves those read modes across serialized plans (lance-format/lance#10759, lance-format/lance#10766). Existing feature flags and unrelated locked packages are unchanged. The release also includes the metric/k-dependent search-effort calibration from lance-format/lance#10695. Update the Node and Python execution tests to its exact probe budgets (for example, effort 0.25 with L2, k=8 and Auto=6 now probes 4 partitions), and cover the 0.1 tier. Recall, caller bounds and probe-precedence assertions remain in place. Validation: - `cargo fmt --all --check` - `cargo clippy --quiet --features remote --tests --examples` - Downstream metadata fixture with SDK source and the released Lance beta.11 path overrides resolves exactly one Lance version. - `cargo test --quiet --features remote --tests`: 2,271 passed, 0 failed, 79 existing ignored tests. - Node native/TypeScript build, lint and API documentation generation passed; 41 query tests passed. - Python native binding build and package Ruff checks passed; 208 query tests passed, 1 slow test deselected, 5 existing deprecation warnings. - Rust results remain applicable: the follow-up changes only binding tests, with product source and dependency graph unchanged from the tested dependency update. Repository-root Ruff currently reports 59 lint findings and 6 formatting failures in untouched documentation snippets. Their blobs match the PR base; the changed Python test and the entire Python package pass lint/format checks.
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