mrubash1 / lancedb

Serverless, low-latency vector database for AI applications

Serverless, low-latency vector database for AI applications

Documentation • Blog • Discord • Twitter

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LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrevial, filtering and management of embeddings.

The key features of LanceDB include:

• Production-scale vector search with no servers to manage.

• Combine attribute-based information with vectors and store them as a single source-of-truth.

• Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.

• Ecosystem integrations: Apache-Arrow, Pandas, Polars, DuckDB and more on the way.

LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.

Quick Start

Installation

pip install lancedb

Quickstart

import lancedb

uri = "/tmp/lancedb"
db = lancedb.connect(uri)
table = db.create_table("my_table",
                         data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
                               {"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
result = table.search([100, 100]).limit(2).to_df()

Blogs, Tutorials & Videos

• 📈 2000x better performance with Lance over Parquet
• 🤖 Build a question and answer bot with LanceDB