wibyuan/easyANN
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.
This project provides a comprehensive comparison of various Approximate Nearest Neighbor (ANN) search algorithms. It helps machine learning engineers and data scientists quickly evaluate different techniques for finding similar data points in large datasets. You input your high-dimensional vectors and get back metrics on how fast and accurately each algorithm finds the nearest neighbors.
Use this if you are a machine learning engineer or data scientist developing a system that relies on finding the most similar items (like products, documents, or images) and need to compare different ANN algorithms' performance trade-offs.
Not ideal if you're looking for a production-ready, highly optimized ANN library to integrate directly into an application without needing to compare multiple implementations.
Stars
12
Forks
1
Language
C++
License
MIT
Category
Last pushed
Jan 22, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/wibyuan/easyANN"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MariaDB/server
MariaDB server is a community developed fork of MySQL server. Started by core members of the...
AlayaDB-AI/AlayaLite
AlayaLite – A Fast, Flexible Vector Database for Everyone.
infiniflow/infinity
The AI-native database built for LLM applications, providing incredibly fast hybrid search of...
nnethercott/hannoy
Production-ready KV-backed HNSW implementation in Rust using LMDB
dingodb/dingo
A multi-modal vector database that supports upserts and vector queries using unified SQL...