Open Source dbdiagram.io Alternatives

Documentation rot is the problem Mermaid was built against. Diagrams cost developer time and go out of date quickly, but going without them hurts productivity and organizational learning, so Mermaid makes the diagram cheap enough to keep current.

It is a JavaScript diagramming and charting tool that pairs Markdown-inspired text definitions with a renderer. Because a diagram is text, it diffs and reviews like code, can be generated inside production scripts, and renders directly in Markdown on GitHub. The Live Editor gives non-programmers a way to build one without touching a build step.

The feature set stays close to that idea.

• Over twenty diagram types: flowchart, sequence, class, state, entity relationship, Gantt, pie, git graph, mindmap, timeline and Sankey among them.
• Customization: themes, colors, fonts and layout directions.
• Sandboxed rendering: a security level renders inside a sandboxed iframe so scripts in user-submitted text cannot execute, at the cost of some interactivity.
• Small footprint: no heavy dependencies to carry into a page.
• Companion projects: a command line interface, the Live Editor and a rendering server.

Public sites that accept diagram text from users are the case the security work addresses, since standard sanitization breaks diagram syntax. Mermaid is MIT licensed, released frequently, and leans on d3 and dagre-d3 for graphical layout. It won a JS Open Source Award in 2019.

drawDB is a database schema editor and SQL generator that runs entirely in a browser tab. Sketching a data model usually means either a heavy desktop modelling tool or a diagram app that knows nothing about SQL, and this sits between the two.

Diagrams are built in a few clicks, and the result is a real entity relationship diagram editor rather than a drawing surface with table shapes on it. No account is needed to use it, so a schema can be sketched and discarded without leaving anything behind.

The parts that matter are the ones connecting a diagram to real SQL.

• SQL export: turn a finished diagram into a script for your database.
• SQL import: bring an existing schema in and get a diagram back from it.
• Migrations: generate migration scripts as the model changes.
• Editor customization: adjust the workspace to match how you work.
• Sharing: optional, and it needs the separate drawDB server plus environment variables set from the sample file.

Running it yourself takes a clone, an npm install and either a dev server or a production build. A Dockerfile is included, so a container build and a port mapping are enough to serve it on a local network. Everything except sharing works from the static build alone, which makes it cheap to keep an instance around for occasional schema work.

Azimutt is a full stack database exploration tool aimed at the schemas real projects accumulate, big and messy, where a standard entity relationship diagram stops being readable. Its authors found that ERDs break down once a schema grows, that data catalogs focus on governance and lineage while missing relational knowledge, and that database clients offer autocompletion and table lists but no visual help.

The backend and admin interface are written in Elixir and Phoenix, while the editor is Elm. Schemas can be written in AML, the modeling language Azimutt uses for fast diagramming, and any public SQL file can be loaded straight from a link, which is how the project offers a badge that opens a repository's structure file in the app.

The tool splits its work into five jobs.

• Design: sketch a schema in AML instead of dragging boxes into place.
• Explore: search everywhere, display only the useful tables and columns, and follow relations.
• Query: navigate data, follow foreign keys, and drop the entities you land on into the diagram.
• Document: attach notes and tags to tables and columns, then save layouts and memos scoped to a feature or a team.
• Analyze: scan the whole database for inconsistencies and for best practices worth applying.

Self-hosting runs from the project's Docker image with a full install guide, and there are a Heroku template and a Kubernetes chart alongside it. Local development needs pnpm, Elm, elm-spa, Phoenix, Elixir, and PostgreSQL. It suits a team that inherited a database nobody fully understands.