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Jack Ye
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Indexing loses its wrapper group -- Overview, Vector Index, FTS Index, Scalar Index and Build & Repair sit directly in Maintenance now, followed by Compaction, Cleanup and Background Jobs at the same level. Cleanup is new, split out of Compaction: pruning old versions is a distinct Enterprise job (cleanup) from merging files (compact), even though optimize() in OSS bundles both into one call. The retention, disk-usage and failed-transaction material that used to live under Compaction's umbrella moves with it. Background Jobs is new and covers what nothing else does: the job types a deployment runs on its own -- WAL/SPFresh maintenance, cache prewarming, registry archiving and metering export, and the object-teardown job that follows a namespace or view drop. Every entry is grounded against the job-coordinator's public job_type constants, not the internal two-letter wire codes used for registry storage. Five existing pages (Build & Repair, Table, Function, Column Refresh, Materialized View Refresh) gain a one-line job-type note rather than duplicating a page for job types they already document. Storage folds into Deployment: storage/index (choosing a backend) and storage/configuration (configuring one) merge into a single Storage page -- they never overlapped, one is the decision and one is the how-to -- and move under Deployment along with Monitoring. Cloud Providers loses its nesting; its two pages plus Azure sit flat, and the former Overview is retitled Deployment Models so it doesn't collide with the group's own Overview entry. Redirects cover every moved URL.
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.
Contributors
Stay in Touch With Us