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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.

Arroy is an open-source library for efficient similarity search and management of vector embeddings, useful in vector database systems.

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

Denser Retriever is a vector-based retrieval system designed for efficient similarity search and information access in AI and ML workloads.

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

A category of vector database solutions and algorithms leveraging graph-based approaches for efficient similarity search and vector indexing, which are core to many vector database implementations in AI applications.

A set of libraries and methods focused on hashing for similarity search in vector databases, directly impacting the performance of large-scale vector search systems.

HVS is a graph-based index structure leveraging Voronoi diagrams for approximate nearest neighbor search in high-dimensional vector spaces. It is directly relevant to vector databases as it provides efficient similarity search capabilities for large-scale vector data.

KGraph is an open-source library for fast approximate nearest neighbor search in high-dimensional vector spaces, applicable to vector database solutions.