> ## Documentation Index
> Fetch the complete documentation index at: https://docs.lancedb.com/llms.txt
> Use this file to discover all available pages before exploring further.

# LanceDB

> Multimodal lakehouse for AI.

**LanceDB** is a [multimodal lakehouse](https://lancedb.com/blog/multimodal-lakehouse/) for
AI, built on top of [Lance](/lance), an open-source lakehouse format. Below, we list a few
ways LanceDB can help you build and scale your AI and ML workloads.

<Steps>
  <Step title="High-performance random access and data management for model training">
    Use LanceDB to curate, explore and distribute very large multimodal datasets for training and fine-tuning models.
    LanceDB comes with built-in table versioning, schema evolution, and fast random access, making it far more efficient to do
    dataset slicing, sampling, filtering and shuffles on large, rapidly evolving datasets.
  </Step>

  <Step title="Massively scalable, fast and high-quality retrieval − without breaking the bank">
    Use LanceDB as the data + retrieval layer for production AI workloads: RAG, agents, semantic search,
    recommendation systems, and more.
    Keep multimodal data, metadata, and embeddings in the same table and query them via vector search,
    full-text search or SQL. Easily add new features (columns in your tables) as your
    application evolves, without copying existing data.
  </Step>
</Steps>

LanceDB is designed for a variety of workloads and deployment scenarios, and supports use cases
that are way beyond traditional vector search. The LanceDB suite includes LanceDB OSS, an open-source embedded library,
and LanceDB Enterprise, a distributed and managed multimodal lakehouse.
Both are built on top of the same open-source Lance format and table abstractions.

<img src="https://mintcdn.com/lancedb-bcbb4faf/KS1PveDlFUMwtlEm/static/assets/images/overview/lancedb-suite.png?fit=max&auto=format&n=KS1PveDlFUMwtlEm&q=85&s=cdcc4a116263d73a17367695b6d048cb" alt="" width="2840" height="760" data-path="static/assets/images/overview/lancedb-suite.png" />

## Use cases

* **Search**: Build high-performance search and retrieval applications using LanceDB's optimized storage, including vector search, full-text search, and hybrid search with secondary indexes.
* **Data Curation**: Manage and filter on petabyte-scale multimodal datasets, including video and point cloud data, to gain insights, explore data and inform model development.
* **Feature engineering**: Add new columns (features), create embeddings, and transform your data at
  scale. LanceDB lets you extend tables both vertically and horizontally with minimal I/O overhead.
* **Training**: Efficiently access and manage large-scale multimodal datasets for training and fine-tuning AI models.

## Choose how you run LanceDB

Depending on your needs, you can choose one of the following ways to run LanceDB.

### 1. LanceDB OSS

The fastest way to get started is the open-source embedded library, with client SDKs in Python, TypeScript
and Rust. Run it locally during development, then use the same data model and APIs as you scale up
and need a managed solution. Start here:

<Columns cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Get started with LanceDB in minutes.
  </Card>

  <Card title="Basic Table Operations" icon="search" href="/tables/">
    Create tables, search vectors, and modify data in LanceDB.
  </Card>
</Columns>

### 2. LanceDB Enterprise

[LanceDB Enterprise](/enterprise) is a distributed and managed **multimodal lakehouse** built for
search, curation, feature engineering, and training-oriented data access workflows
on top of the same core table abstraction. This eliminates the need for teams to build bespoke
infrastructure to manage petabyte-scale multimodal datasets.
To set up LanceDB Enterprise in your organization, reach out to us at
[contact@lancedb.com](mailto:contact@lancedb.com).

<Info>
  **Built with scale, performance, and security in mind.**

  LanceDB Enterprise is designed for very large-scale, high-performance, distributed workloads in
  private deployments, and can operate under strict [security requirements](/enterprise/security).
</Info>

<Card title="Quickstart" icon="rocket" href="/enterprise/quickstart">
  Get started with LanceDB Enterprise in minutes.
</Card>