How KoutenDB uses data locality and placement-aware retrieval to reduce search, RAG, vector search, and LLM context work before ranking begins.
One of the ideas behind KoutenDB is easy to miss if we describe it only as a
NoSQL database, a document store, or a vector-aware storage engine for AI and
search workloads.
The stronger idea is this:
Data locality and data placement can become the first stage of retrieval.
Why KoutenDB uses data locality to retrieve related context when an application knows where to start but cannot enumerate the…
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…
How metadata filtering, tenant scope, and data locality reduce the vector search space before ranking in a RAG database.
A practical RAG database design guide covering SQL, BM25, vector search, reranking, security, cost, and locality-aware context…
This week, I tackled the Search and Retrieval portion of our Local Context Store. If capturing data...
