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README.md

LibreDB Studio — Railway One-Click Template

This folder is the source of truth for deploying LibreDB Studio on Railway as a one-click marketplace template.

Tracking issue: libredb-studio#174

File Purpose
template.json Reviewable serialization of the template service config (image, env vars, volume, healthcheck). Railway does not ingest it directly — see note below.
README.md This file — install + post-install instructions.
PUBLISH.md Step-by-step checklist to create and publish the template in Railway's template editor.
TEMPLATE_OVERVIEW.md Marketplace overview/README pasted into the publish form's "Template Overview" field.
libredb-studio.png 256×256 app logo.

Why no railway.json in the repo? Railway config-as-code only controls how a GitHub repo source is built. Our template uses the prebuilt Docker image ghcr.io/libredb/libredb-studio, so every runtime setting lives in the service definition (captured in template.json), not in a repo config file. A railway.toml would only cause a redundant rebuild of an image CI already publishes.

Deploy

Click the button to deploy from the Railway template marketplace:

Deploy on Railway

Or browse the Railway template marketplace and search LibreDB Studio.

Deploy (manual — works today, before publishing)

Railway dashboard → New Project, then in the project view click + New → Docker Image → enter ghcr.io/libredb/libredb-studio:0.9.22, then configure the service to match template.json:

  • Networking: enable a public domain, target port 3000.
  • Healthcheck path: /api/db/health.
  • Volume: attach one mounted at /app/data.
  • Variables: set the entries from template.json (Railway's variable editor accepts ${{ secret(48) }} / ${{ secret(16) }} for the auto-generated ones).

What the template does

  • Runs ghcr.io/libredb/libredb-studio (pinned version, never :latest) on container HTTP port 3000.
  • Auto-generates a strong JWT_SECRET and admin/user passwords via Railway's secret() function.
  • Persists saved connections & settings with SQLite on a Railway volume (/app/data), surviving restarts and redeploys.
  • Exposes optional AI/LLM fields (Gemini, OpenAI, Ollama, custom) — leave blank to disable.

First login

After deploy, open the service's public domain and log in:

  • Admin (full access incl. maintenance tools): admin@libredb.org + the generated ADMIN_PASSWORD.
  • User (query execution only): user@libredb.org + the generated USER_PASSWORD.

Find the generated passwords in the Railway service's Variables tab.

Add a database to query (optional)

Studio is a client — connect it to any database. To spin one up right next to it on Railway:

  1. In your Railway project: + New → Database → PostgreSQL (or MySQL).
  2. Railway provisions it and exposes DATABASE_URL, PGHOST, PGPORT, PGUSER, PGPASSWORD, PGDATABASE (find them on the database service's Variables tab).
  3. In LibreDB Studio, add a connection using those values (host / port / database / user / password). You can now query it.

Post-install options

Add these variables on the Studio service to extend the deployment:

  • SSO / OIDC — NEXT_PUBLIC_AUTH_PROVIDER=oidc, OIDC_ISSUER, OIDC_CLIENT_ID, OIDC_CLIENT_SECRET, OIDC_ROLE_CLAIM, OIDC_ADMIN_ROLES.
  • PostgreSQL storage backend (multi-node) — STORAGE_PROVIDER=postgres, STORAGE_POSTGRES_URL=....
  • AI — LLM_PROVIDER (gemini | openai | ollama | custom), LLM_API_KEY, LLM_MODEL, LLM_API_URL.

More details and docs: https://github.com/libredb/libredb-studio