mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-13 14:16:54 +00:00
Brendan ClementandClaude Opus 5.5
2347e97e56
## Summary Replaces the generated availability table under **Compare features** on the landing page with a hand-written list of features, grouped by area, with separate Embedded and Enterprise columns. The generated table listed every page that declares `availability`, including overview and basic CRUD pages. Rows such as "Overview" appeared three times without context, and pages like Insert, Update, Database and the integrations showed up as if they were features. | Area | Features | | --- | --- | | Search | Vector, full-text and hybrid search, filtering, reranking, query plans, distributed search | | Indexing | Vector, full-text and scalar indexes | | SQL and curation | SQL, aggregation, sampling, joins, ranking and deduplication, near-duplicate detection, chunking, changes since a version, views | | Feature engineering | Computed columns, materialized views, embedding registry | | Training | PyTorch data loader, permutations, distributed training | | Data management | Branches, compaction and cleanup, background jobs, Real Time engine | | Security | Authentication, authorization | Each ✅/❌ matches the linked page's `availability` on `main`; SQL, which declares none, is Enterprise-only. Functions are left out until it's settled whether they are published. The same list, limited to 1.10 features, is in the Enterprise 1.10 editions in lancedb/docs#398. Checked by assembling the docs site with this change: `mint validate` passes and `mint broken-links --check-anchors --check-redirects` finds no broken links. Vale reports no new warnings. After this merges, the committed `lancedb` skill in lancedb/docs needs a rebuild (`make assemble && make skill`). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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