turbopuffer improves v3 engine performance ninefold with batched reads
Optimizing storage from row-based to column-based postings eliminates inefficient retrieval patterns.
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Vector and full-text search database built on object storage
turbopuffer.comLast updated
In short: turbopuffer raised funding from Thrive Capital, launched major search milestones, and cut prices amid rapid Canadian growth.
Optimizing storage from row-based to column-based postings eliminates inefficient retrieval patterns.
This allows blending date and numeric values with BM25 scoring using sigmoid functions, improving recall without overfetching.
The search engine uses object storage with SSD caching for 100x cheaper cold storage and 10ms warm latency.
New block-based inverted indexes achieve up to 10x size reduction, improving query performance and compression efficiency.
Learn how to synchronize PostgreSQL entities with Turbopuffer using Puffgres. A complete guide on logical replication for efficient vector searches.
Simon Eskildsen, founder and CEO of Turbopuffer, arrives on this podcast with an autobiography that reads like an infrastructure engineer’s origin myth: se...
Ottawa-based Turbopuffer could be a blueprint for the kind of tech company Canada needs to fulfill its AI ambitions ...
Ottawa startup secures funding from Lachy Groom and Joshua Kushner’s Thrive Capital. On the back of a big 2025, Ottawa technology startup Turbopuffer has secured...
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