PhilipJohnBasile/vecstore

Embeddable vector database for Rust and Python. HNSW indexing, metadata filtering, hybrid search, and snapshots. The SQLite of vector search.

43
/ 100
Emerging

This tool helps developers embed fast, intelligent search directly within their applications or even web browsers, without needing a separate server. It takes in various types of data (documents, images, text) as 'vectors' and associated information, and quickly finds the most relevant results based on meaning or keywords. It's ideal for developers building applications that need privacy-focused, offline-capable, or edge-based semantic search.

Use this if you are a developer building an application that needs to perform fast, intelligent searches directly on the user's device or within a browser, without relying on external servers.

Not ideal if you need a fully managed, scalable, cloud-based vector database solution for large-scale, multi-user enterprise applications.

application-development edge-computing offline-apps semantic-search privacy-first
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 13 / 25
Community 11 / 25

How are scores calculated?

Stars

12

Forks

2

Language

Rust

License

Apache-2.0

Last pushed

Feb 03, 2026

Monthly downloads

44

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/PhilipJohnBasile/vecstore"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.