Vector databases · LanceDB, Inc.
LanceDB
Open-source, embedded vector database built on the Lance columnar format for multimodal AI data.
LanceDB is an open-source vector database built around the Lance columnar file format, designed to store and query embeddings alongside the original data (images, text, audio, video) they came from, aimed at multimodal AI and machine-learning workloads rather than text-only RAG. Like DuckDB or SQLite, it runs embedded in-process with no server to manage, reading and writing data directly to local disk or object storage such as S3, which keeps costs low for teams that do not need a constantly running cluster. It supports vector similarity search, full-text search and SQL-style filtering over the same dataset, and versions data so past states can be queried or rolled back. A managed cloud offering, LanceDB Cloud, is also available for teams wanting a hosted serverless version without operating the embedded library themselves. It is best suited to ML teams working with large multimodal datasets who want to avoid duplicating data into a separate vector-only store.
At a glance
| Vendor | LanceDB, Inc. |
|---|---|
| Pricing model | Free tier + paid plans |
| Free tier | Yes |
| Deployment | Cloud, Self-hosted |
| Open source | Yes (Apache-2.0) |
| Best for | ML teams storing embeddings alongside large multimodal datasets who want to avoid running a separate database cluster. |
Pricing
The open-source embedded library is free; a managed LanceDB Cloud service exists but its pricing page did not publish tiers or dollar figures.
Pricing has not been verified yet — see the vendor's site.
Features
- Embedded, serverless-by-default architecture (no cluster required)
- Built on the Lance columnar format for multimodal data
- Vector similarity, full-text and SQL-style filtering in one query
- Direct reads/writes to local disk or object storage (S3)
- Dataset versioning and time travel
- Managed LanceDB Cloud option
Integrations
Profile last reviewed September 21, 2026