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mem0 is an open-source vector database focused on efficient storage and retrieval of high-dimensional embeddings for large-scale AI applications.

MRPT (Multi-Resolution Proximity Trees) is an open-source library for fast approximate nearest neighbor search in high-dimensional vector spaces, applicable to vector database backends.

OasysDB is an open-source vector database focused on efficient similarity search and management of high-dimensional data.

Cottontail DB is an open-source vector database for storing and searching high-dimensional data, with features geared towards research and production environments.

Vexvault is an open-source vector database designed for efficient storage, management, and similarity search of high-dimensional vector data.

An open-source library for approximate nearest neighbor search in high-dimensional spaces, often used as a backend for vector databases and search engines.

K-means Tree is a clustering-based data structure that organizes high-dimensional vectors for fast similarity search and retrieval. It is used as an indexing method in some vector databases to optimize performance for vector search operations.

An influential paper analyzing and improving approximate nearest neighbor search methods for high-dimensional data, highly relevant for developing and understanding vector databases.

Locality-Sensitive Hashing (LSH) is an algorithmic technique for approximate nearest neighbor search in high-dimensional vector spaces, commonly used in vector databases to speed up similarity search while reducing memory footprint.