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LanceDB

Multimodal vector database built on the open source Lance data format

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About LanceDB

LanceDB is an embedded and cloud vector database built on the Lance columnar format, designed for storing and searching embeddings alongside images, video and other multimodal data. It is open source with a managed cloud and enterprise offerings. It targets AI teams building retrieval, search and training data workflows.

Common use cases

  • RAG applications
  • Image and video search
  • Recommendation systems
  • AI training data management

Social listening

What people are saying about LanceDB

Public feedback is limited to a single PeerSpot review from a small-company user who found the open-source edition simple and well documented.

What stands out

  • One reviewer found it simple to adopt with good documentation, using the community edition in the cloud.

Often compared with: Qdrant, Chroma

Sources (1)

Themes summarized from public reviews, community discussion and press coverage as of November 2026. They reflect public discussion, not a rating or an endorsement by AI Connect.

Products and services

LanceDB open source

Embedded vector database library.

LanceDB Cloud

Managed serverless vector database.

LanceDB Enterprise

Distributed deployment with support.

Lance format

Open columnar data format for AI data.

Key features

  • Vector search
  • Multimodal storage
  • Full-text search
  • Embedded operation
  • Object-store backed
  • Versioned datasets

Integrations

  • LangChain
  • LlamaIndex
  • Apache Arrow
  • PyTorch
  • DuckDB
  • Pandas

LanceDB alternatives

FAQs

Is it open source?

Yes, the core library and Lance format are open source.

Can it run embedded?

Yes, it can run in-process inside an application.

Does it handle more than vectors?

Yes, it stores multimodal data and supports full-text search.

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