FreshDiskANN

A 2026 research paper on streaming approximate nearest neighbor search with in-place graph index updates. The approach enables real-time index modifications without expensive rebuilds, crucial for dynamic datasets.

Research on maintaining balanced, high-quality graph indexes while streaming data arrives continuously. Addresses the challenge of index degradation over time with incremental updates.

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.

HVS is an open-source, self-hosted graph-based ANN index using Voronoi diagrams for high-dimensional vector similarity search. Key features include hierarchical graphs, efficient large-scale queries, and free use. Suited for RAG embedding storage/search prototypes, cost-free self-hosting vs Pinecone.

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.