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DBML to ER Diagram

Convert DBML table definitions and refs into a Mermaid ER diagram.

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How to use

  1. 1Paste DBML table definitions with Ref lines for relationships.
  2. 2Review generated ER relationships, join tables, nullable refs, and ownership boundaries.
  3. 3Check whether cardinality matches the product rule before publishing docs.
  4. 4Split large schemas by bounded context or feature area.
  5. 5Export the diagram for product specs, backend reviews, or onboarding notes.

Common use cases

DBML documentationDatabase schema reviewProduct data model discussionER diagram generationAI-generated DBML validation

FAQ

What is DBML to ER Diagram for?

Convert DBML table definitions and refs into a Mermaid ER diagram.

Does it require an account?

No. The tool page can be used directly in the browser.

What makes DBML easier to visualize?

Clear table names, primary keys, Ref lines, and table groups make the ER diagram easier to read and review.

Should I paste a full production schema?

Use a focused subset when writing documentation. Full schemas are better for internal review after removing private names or sensitive comments.

DBML to ER Diagram converts Database Markup Language table definitions and refs into Mermaid ER diagrams for schema documentation and review.

It helps backend and product teams discuss relationships, cardinality, join tables, nullable refs, and tenant boundaries without reading every DBML line.

Use it for focused schema sections, AI-generated DBML validation, and onboarding docs where a visual data model is easier to scan.

Demo: convert DBML refs into ER relationships

DBML is already readable, but an ER preview helps product and backend reviewers see table relationships, ownership, and join tables faster.

  • Include Ref lines for every relationship you want in the diagram.
  • Use table groups or naming conventions for bounded contexts.
  • Preview before pasting schema notes into product docs.
Table users { id int [pk] email varchar }
Table orders { id int [pk] user_id int }
Ref: orders.user_id > users.id

Schema review: use DBML diagrams to discuss cardinality

The diagram should help reviewers ask whether a relationship is one-to-one, one-to-many, or many-to-many, and whether the table design supports the product rule.

  • Look for join tables with missing uniqueness.
  • Check whether nullable refs match real optional behavior.
  • Add notes for soft deletes and tenant boundaries.
Table memberships { user_id int org_id int role varchar }
Ref: memberships.user_id > users.id
Ref: memberships.org_id > organizations.id

Product review: make data ownership visible

DBML diagrams are useful outside pure database review. They help product and platform teams see which entity owns a relationship and where tenant or account boundaries appear.

  • Show account, organization, or workspace tables near dependent tables.
  • Flag shared tables that cross multiple product areas.
  • Add notes for soft-delete or audit-log patterns that are not obvious from refs.
Table accounts { id int [pk] }
Table projects { id int [pk] account_id int }
Table project_members { project_id int user_id int role varchar }
Ref: projects.account_id > accounts.id

Review checklist for DBML to ER Diagram

Use DBML to ER Diagram when you need to inspect source content visually before it becomes documentation, a pull request note, an incident write-up, or a handoff artifact. Convert DBML table definitions and refs into a Mermaid ER diagram.

Before exporting, check that labels are readable, relationships match the source, generated examples do not contain private data, and the preview still makes sense after you edit the input.

Limits and troubleshooting

If the preview fails, reduce the input to the smallest complete example, confirm the format syntax, and then add sections back one at a time. Many rendering failures come from partial files, indentation mistakes, missing diagram headers, or copied snippets that depend on hidden context.

Treat the preview as a review surface rather than a source of truth. Generated diagrams, converted files, dashboards, and rule examples should be checked before they are used in production documentation or operations.

Example inputs to test

  • Commerce: Table users { id int [pk] email varchar } Table orders { id int [pk] user_id int } Ref: orders.user_id > users.id
  • Blog: Table authors { id int [pk] name varchar } Table posts { id int [pk] author_id int title varchar } Ref: posts.author_id > authors.id
  • SaaS: Table accounts { id int [pk] name varchar } Table members { id int [pk] account_id int email varchar } Ref: members.account_id > accounts.id

Tool maturity

Advanced preview

Advanced parser

This tool extracts useful structure and relationships from developer input. Complex edge cases should still be checked against the source.

The maturity label is not a quality score. It tells visitors whether the tool is best for stable export, deeper debugging, quick parsing, or AI-assisted generation.