approximate-nearest-neighbor-search

[NeurIPS'24] Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.

Embedded-first vector database that grows into a self-hosted service and lightweight cluster.

Embedded on-device vector database for AI agent memory and local RAG — disk-based HNSW in an LSM-tree, C++/Python, optimized for low memory footprint

High-Throughput, Cost-Effective Billion-Scale Vector Search with a Single GPU [SIGMOD'26]

Shotit is a screenshot-to-video search engine tailored for TV & Film, blazing-fast and compute-efficient.

Serverless, lightweight, and fast vector database on top of DynamoDB

An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).

This project implements 30+ variants of ANN algorithms to find the K nearest neighbors in high-dimensional vector spaces. It is meant as a convenient sandbox: drop in your own ANN code, run a one-liner, and instantly compare build/search speed and recall against the bundled baselines.

ArcMind Vector DB

High-performance database management system