Cloud vector databases like Pinecone charge and require infrastructure. LanceDB flips that: it runs embedded in your application, no separate server, like a SQLite for vectors. It is a foundation for RAG and similarity search with no operating cost.
What is LanceDB?
Written in Rust and with SDKs for Python, TypeScript and Rust, LanceDB supports vector, full-text and hybrid search, with native support for multimodal data (vectors alongside images, text and metadata) via the fast columnar Lance format.
Key features
- Runs embedded in the app, no server to operate
- Vector, full-text and hybrid search
- Native multimodal data support via the Lance format
- SDKs in Python, TypeScript and Rust
How Reche uses it
Not every product needs a managed, expensive vector database. Reche picks the right architecture for each case, often an embedded solution like LanceDB, to deliver AI with lean cost and no vendor lock-in.