DiskANN - VectorDB Indexing Offload

Language Models are driving petabyte-scale growth? Traditional in-memory indexing strategies quickly exhaust host memory as vector collections expand. DiskANN (Disk-Accelerated Approximate Nearest Neighbor) is a hybrid vector search algorithm developed by Microsoft, designed to offload portions of the search index to NVMe SSDs. It enables scalable approximate nearest neighbor search by intelligently managing a multi-level index—keeping latency-critical portions in memory and using SSDs for the rest, without significant performance degradation.

Attendees will leave with a critical understanding of when and how NVMe-augmented indexing makes sense, plus insights into tuning SSD parameters to sustain high service levels as vector databases continue to scale.