AR
English
Deutsch
Español
Français
Italiano
Português
Nederlands
Polski
Bahasa Indonesia
Русский
Українська
עברית
日本語
한국어DiskANN
Concept
DiskANN is a graph-based approximate nearest neighbor search algorithm from Microsoft Research that keeps a compressed navigation layer in RAM and the full-precision graph on SSD. It is used in services such as Azure Cosmos DB and SQL Server vector search.
| Type | Concept |
|---|
Articles about DiskANN (2)
- Conquering the Billion-Vector Problem in Azure AI Search
· Mirko Peters
Welcome to our deep dive into one of the most pressing challenges in modern enterprise artificial intelligence: scaling vector search to billions of records. If you… - Solving the Billion-Vector Problem in Azure AI Search
· Mirko Peters
Explore the unique technical challenges of searching massive datasets at scale. This post breaks down how high dimensionality and memory constraints impact enterpri…
Community wiki
Short info above, community knowledge below: add practical tips, examples or corrections. New contributions are reviewed first; trusted members publish directly.
Experts and companies for this topic
Nobody has listed this topic yet. Add it to your profile.
Sources
- Profile: www.microsoft.com/research/publication/diskann-fast-accurate-billion-point-nearest-neighbor-search-on-a-single-node
- Feed for this topic (RSS): entity/diskann/feed.xml
- Articles on this topic: 2
Maintained by Mirko Peters (Microsoft MVP) · Last updated: