Updatable Balanced Index for Stable Streaming

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.

An ultra-scalable graph-based nearest neighbor indexing algorithm that builds state-of-the-art indexes up to 11.6× faster than Vamana (DiskANN) and 12.9× faster than HNSW. PiPNN uses HashPrune, a novel online pruning algorithm that enables efficient billion-scale index construction on a single machine.

Fast and accurate graph-based ANN index for streaming similarity search, enabling real-time updates on billion-point indexes using a single machine with real-time freshness.

Real-time indexing of vectors as they arrive in a stream, enabling immediate searchability without batch processing delays. Critical for applications requiring up-to-the-second freshness like social media, news, or real-time recommendations.

An efficient indexing approach for multi-tenant vector databases that handles low-selectivity filters effectively. Curator addresses the challenge of maintaining high performance when serving multiple tenants with filtered vector search queries.

A 2026 research paper presenting graph-based algorithms for diverse similarity search, where results must be both similar to the query and diverse from each other. This addresses the common problem of redundant results in traditional similarity search.