hivellm/vectorizer

A high-performance, in-memory vector database written in Rust, designed for semantic search and top-k nearest neighbor queries in AI-driven applications, with binary file persistence for durability.

39
/ 100
Emerging

This is an in-memory database designed to help developers build AI applications that need to quickly find similar information. It takes in text, images, or other data, processes it into numerical 'vectors,' and then allows for extremely fast searches to find the most relevant items. This is used by software developers and AI engineers who are building applications like smart chatbots, recommendation engines, or intelligent document search systems.

Use this if you are a developer building an AI application and need a fast, reliable, and scalable way to store and search through large amounts of vectorized data, particularly for semantic search or similarity queries.

Not ideal if you are looking for a traditional relational database or a general-purpose NoSQL database for structured data management outside of AI-driven semantic search.

AI-development semantic-search recommendation-systems information-retrieval chatbot-development
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 15 / 25
Community 8 / 25

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Stars

19

Forks

2

Language

Rust

License

Apache-2.0

Last pushed

Mar 09, 2026

Commits (30d)

0

Get this data via API

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

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