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What does it do?

  • Vector Database
  • Multi-modal Data Management
  • Vector Similarity Search
  • SQL Querying
  • Data Versioning

How is it used?

  • images
  • Install the SDK
  • query multi-modal data with SQL.
  • 1. Access web app
  • 2. Integrate w/ API & SDK
See more

Who is it good for?

  • Machine Learning Engineers
  • Data Scientists
  • AI Developers
  • NLP Researchers
  • Computer Vision Specialists

What does it cost?

  • Pricing model : Book Demo / Request Quote

Details & Features

  • Made By

    LanceDB
  • Released On

    2022-10-24

LanceDB is an open-source vector database designed for AI applications, offering efficient storage, management, querying, and retrieval of embeddings for large-scale multi-modal data. It supports various data types including text, images, and videos directly within the database, eliminating the need for separate storage solutions.

Key features:
- Multi-modal Data Support: Directly stores and manages various data types like text, images, videos, and point clouds alongside their embeddings.
- Vector Search: Enables production-scale vector similarity search, full-text search, and hybrid search capabilities.
- SQL Query Interface: Integrates with DataFusion to provide SQL querying capabilities.
- Automatic Data Versioning: Manages versions of data automatically, simplifying data management without additional infrastructure.
- Disk-based Index & Storage: Allows for scalable storage solutions that are cost-effective.
- Ecosystem Integrations: Supports integration with tools like Apache Arrow, Pandas, Polars, DuckDB, and more, facilitating seamless data operations.
- Language Support: Native support for Python, JavaScript/TypeScript, and Rust, catering to a wide range of developers.

How it works:
1. Store multi-modal data and embeddings in LanceDB.
2. Use vector search capabilities to query and retrieve relevant information.
3. Leverage SQL interface for complex queries and data analysis.
4. Utilize automatic versioning for data management.
5. Integrate with other tools and platforms as needed.

Integrations:
Apache Arrow, Pandas, Polars, LangChain, LlamaIndex, DuckDB

Use of AI:
LanceDB leverages generative AI to enhance its vector search capabilities, making it compatible with various AI applications for improved data retrieval and management processes.

Target users:
- Developers working on AI and machine learning projects
- Enterprises handling large-scale, multi-modal data
- Teams focused on natural language processing, computer vision, or personalized recommendation systems

How to access:
LanceDB is available as a web application for cloud-based interactions and as an API and SDK for integration into existing applications. The open-source version can be run locally or on a user's server, while the cloud version offers a serverless solution.

Versions:
- Open-source embedded version: Runs in-process
- Cloud-based SaaS solution: Offers serverless capabilities

Licensing:
LanceDB is available as an open-source project under the Apache-2.0 license, allowing developers to modify, distribute, and use the software in their own projects.

  • Supported ecosystems
    Unknown
  • What does it do?
    Vector Database, Multi-modal Data Management, Vector Similarity Search, SQL Querying, Data Versioning
  • Who is it good for?
    Machine Learning Engineers, Data Scientists, AI Developers, NLP Researchers, Computer Vision Specialists

PRICING

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Pricing model: Book Demo / Request Quote

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