Ross ROSS = Recommend OSS · open-source software intelligence for agents

azimuttapp/azimutt

Explore, document and optimize any database observed · 2026-08-28

github.com/azimuttapp/azimutt · homepage · Elm · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

77/100

  • Activity 99
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1836
  • days_rel: n/a
  • days_push: 8
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

2170 stars · 141 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Azimutt is a full-stack database exploration tool offering a next-generation ERD that scales to large, messy real-world schemas, plus data navigation, documentation, and schema analysis. It supports many databases (PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Couchbase, and more) via its own tolerant SQL parser and schema inference, and can be used through its web app or a local CLI.

Use cases

  • visualize erd of a large database with hundreds of tables
  • document database tables and columns with notes and memos
  • find join paths between two tables
  • design a database schema quickly with a DSL
  • lint database schema for missing primary keys and foreign keys
  • explore data by following relations across tables
  • import a sql dump to generate a diagram
  • onboard a developer to an unfamiliar database schema

When to choose

  • you need to explore or document a large, complex relational or document database schema
  • traditional ERD tools choke on schemas with hundreds or thousands of tables
  • you want contextual documentation (notes, memos, SQL comments) attached to tables and columns
  • you want automated schema quality checks like missing PKs/FKs and type inconsistencies
  • you need to share interactive diagrams with your team or embed them in docs

When to avoid

  • you only need a simple SQL query client with autocomplete
  • you need full data governance, lineage, or cataloging features of enterprise data catalogs
  • you require deep support for a niche database not covered by its SQL parser or JSON import
  • you need offline-only collaboration without any hosted component for sharing

Facets

application · maturity active

database search-engine data-visualization documentation parser developer-tools databases developer-tools documentation data-visualization web-development self-hosted cli cross-platform erd database-diagrams schema-exploration aml database-documentation schema-linter elm database-client web-server

10 sources

Member repositories

RepositoryRoleHealth v2
azimuttapp/azimuttmain77

For agents

markdown · JSON · MCP: product_card(name="azimuttapp/azimutt")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem