Weaviate: Vamana vs. HNSW - Disk-Based ANN Algorithm Exploration

AI Impact Summary

Weaviate is exploring Vamana, a disk-based ANN algorithm, as an alternative to its current HNSW implementation to address the challenge of scaling vector search beyond available RAM. Vamana builds a flat graph, optimizing for efficient disk access by storing node positions directly, while HNSW uses a hierarchical representation for faster traversal. This shift represents a strategic move to support increasingly large datasets and query loads, potentially offering a more cost-effective solution for use cases where latency requirements aren't paramount.