Why SQLite+FTS5 beats Vector DBs for AI Agent Memory

The conventional wisdom is wrong Everyone says you need a vector database for AI memory. Pinecone, Weaviate, Qdrant. They all need a server, an API key, and a monthly bill. I went a different way: SQLite + FTS5 . One file. Zero dependencies. Better results. How it works BrainDB stores 4,300+ memories in a single SQLite file with three search modes: 1. Full-text search (FTS5) — Sub-millisecond keyword search with BM25 ranking. 2. Embedding similarity — 384-dim vectors stored as BLOBs, cosine similarity computed in TypeScript. 3. Hybrid search — Reciprocal Rank Fusion combines both for best-of-both-worlds retrieval. Custom relevance scoring SQLite custom functions run type-aware ranking inside the database: Decisions get +0.3 boost (authoritative) Issues get -0.1 (often resolved) Superseded memories return 0 Exponential time decay with type-specific half-lives The numbers Metric SQLite+FTS5 Pinecone Free Latency <1ms 50-200ms Setup 0 minutes 15 minutes Cost $0 $0-70/mo Backup cp file.db