1
RIP, vector database
turbopuffer is pushing the frontier of search. To do that, we have to fundamentally redesign our storage architecture so the vector index is no longer primary.
turbopuffer Blog
vector and full-text search built on object storage: fast, 10x cheaper, and extremely scalable
- Popular posts
- 4
- Total points
- 1,064
- HN comments
- 282
- Rank
- #1,218 company
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Databases & Data 4Infrastructure & DevOps 2Tech Industry & Business 1AI & Machine Learning 1
2
Turbopuffer: Fast search on object storage
Inaugural blog post about the development of turbopuffer, a search engine that uses object storage and SSD caching for cost-effective, low latency search. This post describes into the motivation behind its creation, its unique architecture, and how it significantly reduces costs for large-scale vector searches…
3
A distributed queue in a single JSON file on object storage
How to build a single global queue for distributed systems on object storage: Start with a single file on object storage, then add write batching, a stateless broker, and high-availability.
4
ANN v3: 200ms p99 query latency over 100B vectors
Our latest ANN release supports scales of 100+ billion vectors in a single search index, with 200ms p99 query latency at 1k QPS and 92% recall.