Starling

Adanns is a framework for adaptive semantic search, focusing on efficient and scalable similarity search in high-dimensional vector spaces. Its relevance to 'Awesome Vector Databases' lies in its support for advanced vector search techniques suitable for AI and machine learning applications.

Cagra provides highly parallel graph construction and approximate nearest neighbor search for GPUs, supporting large-scale vector database operations and efficient similarity search.

iRangeGraph is an ANN indexing approach and accompanying implementation for range-filtering nearest neighbor search. It provides a specialized graph-based index that supports vector similarity search under range constraints, making it directly useful as a component or reference implementation for advanced vector database indexing and retrieval.

NSG is an approximate nearest neighbor search algorithm based on a sparse navigable graph structure designed for high-dimensional vector similarity search. The reference implementation provides a graph-based ANN index that can be integrated into custom vector retrieval systems.

Epsilla is an open-source vector database optimized for high-performance similarity search and scalable storage of vector embeddings.

MuopDB is an open-source vector database designed for fast and scalable similarity search in AI applications.