LanceDB
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Open-source embedded multimodal vector database built on the Lance columnar format.
LanceDB is an embedded retrieval library for multimodal AI that runs in-process and can persist data locally or in cloud object storage. It stores vectors, metadata, and raw multimodal data (text, images, video, point clouds) together in the Lance format, with automatic versioning and zero-copy access. It supports vector similarity search, full-text search, and SQL filtering, with client SDKs for Python, TypeScript, and Rust. A managed LanceDB Enterprise offering is available for distributed, large-scale production deployments.
Strengths
- Embedded/serverless design needs no separate server to operate
- Stores raw multimodal data alongside vectors with built-in versioning
- Multiple query modes in one engine: vector, full-text, and SQL
- Open source with native SDKs for Python, TypeScript, and Rust
Tradeoffs
- Embedded model fits single-node/edge use better than large multi-tenant clusters
- Requires bringing your own embedding model for vector generation