doganarif/vectordb

In-memory vector database with pluggable indexing algorithms, metadata filtering, and a FastAPI-based REST API.

26
/ 100
Experimental

This project helps developers build applications that can quickly find similar items based on their characteristics. You input collections of numerical vectors (embeddings) representing text, images, or other data, along with descriptive information (metadata). The system then lets you swiftly search these collections for the most similar vectors, filtered by their metadata. It's designed for software engineers building features like recommendation engines or semantic search.

No commits in the last 6 months.

Use this if you are a software developer needing a fast, in-memory system to store and search high-dimensional vectors for similarity, especially when building prototypes or applications that don't require shared state across multiple backend processes.

Not ideal if you need a production-ready, distributed vector database that scales horizontally across multiple servers and shares data consistently without extra configuration or implementing a custom persistent repository.

semantic-search recommendation-engine information-retrieval vector-similarity-search application-development
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 7 / 25
Community 12 / 25

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Stars

11

Forks

2

Language

Python

License

Last pushed

Aug 18, 2025

Commits (30d)

0

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