---
id: lancedb
version: "0.37.1"
license: unclear
license_treatment: permissive
maintenance: active
---

# lancedb — lancedb

License: permissive · Maintenance: active · Downloads: 8.2M/mo

## What it is and what it does

LanceDB is a Python client library for the Lance vector database, enabling developers to store, index, and search high-dimensional embedding data. It wraps the embedded Lance storage engine (written in Rust) and exposes a Python API for connecting to datasets, opening tables, and executing vector similarity searches with optional result limits.

The package depends on numpy, pyarrow, pydantic, and other utilities for data handling and serialization. It ships as a compiled wheel targeting modern x86_64 hardware (Haswell baseline with AVX2), but offers a separate lancedb-compat distribution for older processors that lack AVX2 support. The library is in alpha status and receives regular updates; preview releases are available for early access to new features.

Use it for:

- Build semantic search features by indexing embeddings and querying them with vector similarity
- Store and retrieve machine learning model outputs (embeddings) efficiently for retrieval-augmented generation
- Prototype vector database workflows without managing a separate server process
- Integrate vector search into data science pipelines using PyArrow-compatible data formats

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

LanceDB is a Python SDK for connecting to and querying LanceDB vector databases, supporting search operations on embedded data with filtering and result limits.

Yes, if you need embedded vector search in Python and can meet the Python 3.10+ requirement. The active maintenance, permissive license, and zero known vulnerabilities make it low-risk. Medium install friction is manageable for most modern systems; pre-Haswell x86_64 users must use lancedb-compat. Alpha status means the API may change, but frequent releases and high GitHub stars suggest a maturing project.

## Install

pip install lancedb
uv add lancedb
poetry add lancedb

## Installing lancedb

Before you install: Medium install friction due to compiled native wheels (Rust-based lance crate). Requires Python 3.10+. Pre-Haswell x86_64 systems need the separate lancedb-compat package to avoid illegal instruction crashes; standard wheels target x86-64-haswell. Active maintenance with releases every 2 weeks; latest release 4 days old.

License in practice: Apache 2.0 permissive license allows commercial and private use with minimal restrictions.

Quickstart:

pip install lancedb

import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()

Requires Python 3.10+. Pre-Haswell x86_64 hosts must install lancedb-compat instead to avoid illegal instruction errors; standard wheels target x86-64-haswell baseline.

Verify before relying:

- Whether the package supports remote LanceDB servers or only local file-based datasets
- Performance characteristics and scalability limits for large vector datasets
- Full API surface beyond basic search (filtering, aggregation, updates)

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 8.2M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

vector database python client, lance db sdk, embedding search library, vector similarity search, arrow-based data store, machine learning data retrieval, semantic search python, vector-search, embeddings, arrow-native

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