Why KoutenDB uses data locality to retrieve related context when an application knows where to start but cannot enumerate the full result in advance.
Most database queries begin by describing the answer.
You provide a primary key, write a SQL predicate, select a collection, enter
search terms, or send an embedding to a vector database. The database then
finds the records that match.
That model works extremely well, but it is not the shape of every application
How KoutenDB uses data locality and placement-aware retrieval to reduce search, RAG, vector search, and LLM context work before…
A development note on KoutenDB v0.6 planning: safer filter builders, deeper physical locality validation, topology improvements,…
KoutenDB v0.9.0 adds disk-backed locality validation, bounded related-data reads, and reproducible benchmarks for a ring-oriented…
Companies like Spotify need vast quantities of data accessible at low latency for online services and, increasingly, AI Agents…
Search through billions of items for similar matches to any object, in milliseconds. It’s the next generation of search, an API…
Why your queries are slow and how the right index fixes it — B-trees, composite indexes, and the EXPLAIN habit every developer…
