LoRANN

A C++ library for performing fast approximate nearest neighbor searches in high dimensional spaces. Contains multiple ANN algorithms and automatic algorithm selection based on dataset characteristics.

Advanced algorithm designed to make hybrid searches combining metadata filters and vector similarity more efficient, implemented in Apache Solr and other vector search systems.

Optimization technique that allows HNSW vector searches to exit early when the candidate queue remains saturated, reducing latency and resource usage with minimal recall impact.

A graph-based approximate nearest neighbor search algorithm that uses both long-range and short-range links to achieve poly-logarithmic search complexity. Foundation for the more advanced HNSW algorithm.

A major algorithmic advancement to Google's ScaNN that introduces controlled redundancy to the vector index, leading to improved search efficiency. Enables even faster vector search while maintaining or improving accuracy.

Graph-based algorithm for approximate nearest neighbor search that maintains multi-layer graph structures for efficient vector similarity search with logarithmic complexity, widely used in modern vector databases.