×

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

    2022-08-27

LanceDB is a cutting-edge, open-source vector database tailored for AI applications, emphasizing ease of use, scalability, and cost-effectiveness. Launched by Y Combinator in early 2023, LanceDB is designed to store, manage, query, and retrieve embeddings on large-scale multi-modal data efficiently. It supports a variety of data types including text, images, videos, and more, directly within its database, eliminating the need for separate storage solutions.

Availability
LanceDB is available in two versions:
- Open-source, embedded version that runs in-process
- Cloud-based SaaS solution that offers serverless capabilities

This flexibility makes it an ideal choice for developers and businesses looking to integrate advanced vector search capabilities into their applications without the overhead of managing complex infrastructure.

Features and Capabilities
- 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

Supported Integrations
LanceDB integrates with several key technologies and platforms:
- Apache Arrow: For zero-copy access in shared memory with SIMD and GPU acceleration
- Pandas and Polars: For direct ingestion of data frames
- LangChain and LlamaIndex: Enhancing capabilities in natural language processing and vector indexing
- DuckDB: For additional database management features

Ideal Users
LanceDB is ideal for developers and enterprises involved in AI and machine learning projects that require efficient handling of large-scale, multi-modal data. It is particularly useful for applications in areas such as natural language processing, computer vision, and personalized recommendation systems.

Open Source Status
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

Visit site
Pricing model: Book Demo / Request Quote

Alternatives

BlackBox AI is an AI-powered coding assistant that helps developers write code faster using autocomplete, generation, and search features.
Automate workflows by connecting APIs, AI, databases with code or no-code options.
Langfuse provides tools for teams to build, debug, and improve large language model applications.
Buster is an AI platform that converts natural language queries into SQL commands for databases.
Unify.ai provides a single API to access and combine multiple large language models, optimizing performance based on user-defined criteria.
Superpowered.ai is an AI platform that integrates LLMs with user data to generate accurate, cited responses for various domains.
Lantern is a high-performance, cost-efficient vector database for developers to build AI apps easily.
Helicone is an open-source observability platform for developers working with Large Language Models.
UpTrain is an open-source LLMOps platform that streamlines evaluation, experimentation, and regression testing for developers working with large language models.
SciPhi simplifies the development, deployment, and scaling of Retrieval-Augmented Generation (RAG) systems.