#55th of 13 in Vector databases
lancedb
Embedded vector database built on the Lance columnar format
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- Stars
- 11.7k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Rust
9,629 on 31 Mar 202611,721 on 20 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
LanceDB is a vector database written in Rust on top of the Lance columnar format. It stores vectors, metadata and multimodal data (text, images, video, point clouds) and supports vector similarity search, full-text search and SQL filtering. It runs locally or in your own cloud, with Python, TypeScript and Rust SDKs plus a REST API.
Who it is for: Developers needing an embedded vector store for multimodal AI apps
Ranked among open-source alternatives to Pinecone (#5 of 10).
Strengths
- Runs embedded and locally, with no separate server required per the README
- Combines vector search, full-text search and SQL in one store
- Automatic data versioning and zero-copy access without extra infrastructure
- Python, TypeScript and Rust SDKs; integrates with LangChain, LlamaIndex, Pandas, Polars, DuckDB
Weaknesses
- README gives no benchmarks or hardware figures to back the billion-vector claims
- Managed Cloud and Enterprise tiers exist; feature split with open source is not detailed
- README has little setup detail and defers to external docs
- RAM and GPU requirements are not stated
What it needs
- GPU optional
- Docker + Compose
Also in Vector databases
See all 13| Rank | Project | Score |
|---|---|---|
| 1 | MilvusDistributed vector database with dense, sparse and hybrid search at scale | 82 out of 100 |
| 2 | MeilisearchRust search engine with typo tolerance, filtering and hybrid semantic search | 75 out of 100 |
| 3 | QdrantRust vector database with payload filtering, REST and gRPC | 69 out of 100 |
| #4 | faissC++ library for similarity search and clustering of dense vectors | 66 out of 100 |
| #6 | ChromaEmbedding database with a four-function API for Python and JavaScript | 63 out of 100 |