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**
```shell
pip install lancedb
```
**Quickstart**
```python
import 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]).where("price < 15").limit(1).to_df()
```
**Serverless, low-latency vector database for AI applications**
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