A curated list of awesome projects and research related to vector search, including dedicated vector databases, vector search libraries, performance benchmarks, and cost analysis resources.

A curated list of tree-based approaches and systems for vector indexing and search, foundational for certain types of vector databases.

A curated collection of libraries, services, and research papers focused on vector search, including vector database technologies and related resources.

Puck is an open-source vector search engine designed for fast similarity search and retrieval of embedding vectors.

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

This work by Jingfan Meng is a comprehensive research thesis on efficient locality-sensitive hashing (LSH), covering algorithmic solutions, core primitives, and applications for approximate nearest neighbor search. It is relevant to vector databases because LSH-based indexing is a foundational technique for scalable similarity search over high-dimensional vectors, informing the design of vector indexes, retrieval engines, and similarity search modules in modern vector database systems.