Monlite unifies vector store, cache, and job queue in a single SQLite file

A developer frustrated by multi-container local setups for AI agent projects built Monlite, a TypeScript library that consolidates document storage, vector search, full-text search, key-value cache, job queue, and cron scheduling into one SQLite file. The library uses SQLite's built-in capabilities — including ACID transactions, WAL mode, and the FTS5 engine — along with the sqlite-vec extension for KNN vector queries. A key engineering challenge was ensuring exactly-once job claiming across multiple worker processes, solved using SQLite's BEGIN IMMEDIATE write-intent lock rather than optimistic locking. Monlite also supports cross-language interoperability, allowing Python and Node.js to read and write the same database file with verified round-trip tests. Now at version 2.6.1 with a stable API, the project is explicitly designed for single-machine local workloads, with an optional sync package available for replication to cloud databases like MongoDB or Postgres.