Adanns

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

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.

Starling is an I/O-efficient, disk-resident graph index framework tailored for high-dimensional vector similarity search on large data segments, supporting the scalable storage and retrieval needs of vector databases.

A research group focused on advancing the theory and practice of vector databases, providing resources, publications, and tools related to vector database technology.

Applied book on using deep learning for search, including dense vector representations, semantic search, and neural ranking, all directly relevant to building applications on top of vector databases.

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