explaingit

qataruts/monlite

Analysis updated 2026-05-18

38TypeScriptAudience · developerComplexity · 3/5LicenseSetup · easy

TLDR

A single-file, SQLite-backed backend for TypeScript apps and AI agents that bundles a document database, vector search, job queue, cache, and cron into one API.

Mindmap

mindmap
  root((monlite))
    What it does
      One file backend
      SQLite underneath
      Mongo style API
    Tech stack
      TypeScript
      SQLite
      Postgres option
    Use cases
      AI agent memory
      Vector search
      Job queues
    Audience
      Developers
      Agent builders
    Extras
      Realtime live queries
      Studio inspector UI
      Zero config

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Give an AI agent memory, semantic search, a job queue, and locks using one local file instead of four separate services.

USE CASE 2

Replace MongoDB, Elasticsearch, Redis, and BullMQ in a small app with one SQLite-backed package.

USE CASE 3

Query typed document collections with a MongoDB or Prisma style API, including transactions and grouped aggregation.

USE CASE 4

Subscribe to live query results in an app, similar to Firebase's realtime database.

What is it built with?

TypeScriptSQLiteNode.jsPostgreSQL

How does it compare?

qataruts/monlitedjdeveloperr/nativescript-expojavlonbek1233/-bento-grid
Stars383838
LanguageTypeScriptTypeScriptTypeScript
Setup difficultyeasymoderateeasy
Complexity3/54/51/5
Audiencedeveloperdevelopervibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

monlite is a database and backend toolkit for TypeScript projects, especially ones building AI agents, that packs everything into a single file on disk. Instead of running a separate database server, it uses SQLite under the hood while offering an API that feels like MongoDB, with the developer experience of a tool like Prisma. There is no server to start, no configuration file to write, and no database migrations to manage. You point it at a file and it works, and the same code can later run against a networked Postgres database if a project outgrows a single file. The project's main pitch is that an AI agent, a retrieval pipeline, or a background worker usually needs several separate pieces: a document store for memory, semantic vector search, a job queue, and simple locks to avoid duplicate work. Normally that means running four different services together with a tool like Docker Compose. monlite bundles all of that into optional add-on packages that sit on top of the same single file: full text search, vector similarity search for semantic memory, a durable job queue with retries and deduplication, a key-value cache with locks, a cron-style scheduler for recurring jobs, and a realtime layer for pushing live updates to clients. Data is organized into typed collections queried with a familiar Mongo or Prisma style syntax, supporting filtering, grouped aggregation, atomic updates, and multi-step transactions. A live query feature lets an application subscribe to a collection and get notified only when something relevant actually changes, similar to how Firebase's realtime database works. A small companion tool called monlite studio opens a local web interface for browsing the data inside a database file without writing any code. This project is aimed at developers building agents, command-line tools, or small to medium applications who want to avoid setting up multiple backend services during early development. It is released under the MIT license, so it can be reused freely, including for commercial projects, as long as the copyright notice is preserved.

Copy-paste prompts

Prompt 1
Set up monlite with the vector and queue plugins so my AI agent has memory, semantic recall, and a job queue in one file.
Prompt 2
Show me how to write a typed collection query with a where clause and grouped aggregation in monlite.
Prompt 3
Explain how monlite's watch() function decides when to re-emit a live query result.
Prompt 4
Help me migrate my monlite app from a single SQLite file to the Postgres backend when it outgrows one file.

Frequently asked questions

What is monlite?

A single-file, SQLite-backed backend for TypeScript apps and AI agents that bundles a document database, vector search, job queue, cache, and cron into one API.

What language is monlite written in?

Mainly TypeScript. The stack also includes TypeScript, SQLite, Node.js.

What license does monlite use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is monlite to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is monlite for?

Mainly developer.

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