Tools/libredb/libredb-studio

libredb-studio

One browser tab for PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, Redis, SQLite, Couchbase, ClickHouse, Druid, DuckDB, Turso and more. An open-source SQL IDE with SSO, audit trail and AI-assisted queries MIT licensed, with nothing held back behind an enterprise wall.

1.2k ★+49/wkemergingTypeScriptMIT License →trending

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Oct 2026

LibreDB Studio is a database editor that lives in a browser tab instead of on your laptop. Deploy it next to your databases and the whole team opens a URL to query Postgres, MySQL, SQL Server, Oracle, MongoDB, Redis, DuckDB and dozens more. It's MIT licensed, with no paid edition.

Setup is one docker run or npx @libredb/studio. For a team, change two defaults: point storage at SQLite or Postgres (otherwise saved connections live in each person's browser), and set your own admin credentials. OIDC single sign-on, roles, a query audit trail and ER diagrams all ship free.

Solo: free, though DBeaver or Beekeeper Studio is simpler on one machine. Small teams: free, and the sweet spot: one container inside the network, no SSH tunnels. Larger teams: free, but SAML is still on the roadmap and you're patching a server that holds every database password.

The catch: it's ten months old, still 0.x, ships releases almost daily, and one maintainer wrote most of the code. Data masking only hides values on screen, not in the API. Turn on the AI features and your schema, plus real min/max values from profiled columns, go to whatever model you configure.

Free vs Self-Hosted vs Paid

fully free

Free: Everything. The MIT build includes OIDC single sign-on, role-based access control, the query audit trail, ER diagrams, schema diff, the monitoring dashboard and the AI features. The project states there is no paid edition and no hosted offering.

Self-hosted: Docker image on GHCR (mirrored to Docker Hub), a Helm chart, npx @libredb/studio (Node 24+), Homebrew, Snap, winget, Chocolatey, Scoop, .deb/.rpm with a systemd service, and Linux desktop builds (AppImage, .deb, Flatpak). Default storage keeps connection metadata in the browser; set STORAGE_PROVIDER=sqlite or postgres for a shared team install.

Paid: No paid tier. The only optional cost is an LLM: Gemini is the default, OpenAI or any OpenAI-compatible endpoint also work, or run a local model through Ollama for free. With no LLM_* settings, the AI features stay off.

Free at every team size with SSO, RBAC and audit included; the only spend is an optional LLM API key if you want the AI agent, and a local Ollama model avoids even that.

What to do by team size

Solo
free; one docker run, though a desktop client may be simpler for one person
Small team
free; one container inside the private network replaces SSH tunnels on every laptop
Medium team
free with OIDC SSO and audit trail; switch storage to Postgres and set explicit credentials
Large team
free, but no SAML yet and it's young; treat it as a server holding every DB credential and harden it
Self-hosting ops:moderate

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Score
72/100 · B+
Adoption13/30
Maintenance25/25
Community9/20
License15/15
Analysis10/10

A low score is not a verdict on quality. Young and niche tools start low by design. How we calculate scores

Trust Signals

Community discussions enabledOrganization account (31 public repos)

License: MIT License

Use freely, including commercial. Just keep the license.

Commercial use: ✓ Yes

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