A curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search
- Qdrant - Vector Similarity Search Engine with extended filtering support
- Pinecone - Similarity Search as a Service
- Vald - A Highly Scalable Distributed Vector Search Engine
- Milvus - An open source embedding vector similarity search engine powered by Faiss, NMSLIB and Annoy
- Weaviate is a cloud-native, real-time vector search engine
- OpenDistro Elasticsearch KNN - A machine learning plugin which supports an approximate k-NN search algorithm for Open Distro for Elasticsearch
- Elastiknn - Elasticsearch plugin for nearest neighbor search
- Vearch is a scalable distributed system for efficient similarity search of deep learning vectors
- pgANN - Fast Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database
- Faiss - A library for efficient similarity search and clustering of dense vectors
- ScaNN - A library efficient vector similarity search at scale.
- NMSLIB - Non-Metric Space Library, an efficient similarity search library for generic non-metric spaces
- Annoy - C++ library with Python bindings to search for points
- FLANN - library written in C++ and contains bindings for the following languages: C, MATLAB, Python, and Ruby
- MRPT - fast nearest neighbor search with random projection
- RPForest - Python library for approximate nearest neighbours search
- NGT - provides commands and a library for performing high-speed approximate nearest neighbor
- NearPy - approximate search using different locality-sensitive hashing methods
- TOROS N2 - lightweight approximate Nearest Neighbor library
- PUFFINN - Parameterless and Universal Fast FInding of Nearest Neighbors
- SPTAG - A distributed approximate nearest neighborhood search (ANN) library
- PyNNDescent - A python nearest neighbor descent for approximate k nearest neighbors
- TarsosLSH - A Java library implementing practical nearest neighbour search algorithm for multidimensional vectors
- TorchPQ - Efficient implementations of Product Quantization and its variants using Pytorch and CUDA
- Accelerating Large-Scale Inference with Anisotropic Vector Quantization
- Billion-scale similarity search with GPUs
- Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
- Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data
- On Approximately Searching for Similar Word Embeddings
