FreshDiskANN

Incremental in-place update system for billion-scale vector search from Microsoft Research. Maintains 2.41x lower P99.9 latency than baselines while supporting efficient vector updates with minimal resource overhead.

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.

Leading graph-based ANN library optimized for approximate nearest neighbor search, offering competitive performance especially at lower recall levels across diverse datasets.

Performant and predicate-agnostic search algorithm for vector embeddings with structured data. Uses two-hop graph expansion to maintain high recall under selective filters in Weaviate.

Graph-based similarity search algorithm achieving 0.99 recall, building indexes 3-8x faster than competitors with 40% less memory. Answers 1-NN queries up to 10x faster than serial scan.

Hierarchical Clustering-based Nearest Neighbor Graph using MST to connect dataset points through multiple hierarchical clusters. Performs efficient guided search instead of traditional greedy routing.