holistics/dbml

Database Markup Language (DBML), designed to define and document database structures

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Summary Information

Updated 59 minutes ago
Added to GitGenius on September 18th, 2026
Created on March 24th, 2019
Open Issues & Pull Requests: 106 (+0)
GitHub issues: Enabled
Number of forks: 233
Total Stargazers: 3,706 (+0)
Total Subscribers: 37 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.1 days
Mean response time: 222.6 days
90th percentile: 1124.6 days
Tracked items: 101

Most active contributors

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How this project is maintained

98% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "bug" is answered fastest, typically in about 17 hours, while "enhancement" waits about 5 days. Three people close 74% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 55
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,090 days
Stale 30+ days: 54
Stale 90+ days: 52

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (40)
  • bug (24)
  • help wanted (10)
  • good first issue (7)
  • question (3)
  • PR: Refactor :broom: (1)
  • pkg: core (1)

Most active issues this week

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Detailed Description

DBML is a domain-specific language for defining and documenting database schemas in a human-readable format.

DBML addresses the problem of writing database schemas in a way that is both easy to read and independent of any particular database system. Rather than forcing developers to learn the specific syntax of SQL dialects, DBML provides a simple, flexible notation that captures the essential structure of a database: tables, columns, data types, primary keys, and relationships. The language focuses on clarity and simplicity, abstracting away database-specific details while remaining expressive enough to document the core design.

Teams should adopt DBML if they need to document database schemas in a format that is accessible to both technical and non-technical stakeholders, or if they want a database-agnostic way to define schemas before committing to a specific database system. The tool works well for projects where schema visualization and documentation are priorities. DBML integrates with free hosted tools: dbdiagram.io provides visual database diagrams, and dbdocs.io offers database documentation generation. The ecosystem includes community-maintained parsers and schema generators in multiple languages, making it possible to integrate DBML definitions into existing development workflows and generate schemas for different database systems.

The project maintains an active ecosystem page where community members can register tools that read or write DBML, and contributions are welcomed through pull requests. Development activity shows consistent engagement with schema definition features and tooling integrations across the broader DBML ecosystem.