Key Facts
- Category
- Development
- Input Types
- textarea, select
- Output Type
- json
- Sample Coverage
- 4
- API Ready
- Yes
Overview
Database Schema Diff compares two schema definitions and turns the gap into a migration-oriented report covering tables, columns, indexes, and foreign keys.
When to Use
- •When you need to understand how one database schema differs from another.
- •When release planning depends on knowing which DDL changes are required.
- •When teams want a migration draft before applying changes in MySQL, PostgreSQL, or SQLite.
- •When reviewing schema updates in pull requests or handoff documents.
How It Works
- •Paste the current schema and the target schema in SQL DDL or JSON/YAML summary form.
- •The tool parses tables, columns, indexes, and foreign keys from each side.
- •It compares added, removed, and changed elements between the two versions.
- •The output includes a structured change list, a migration SQL draft, and visualization-ready relationship data.
Use Cases
Examples
1. Review a schema migration before deployment
Backend engineer- Background
- A service branch adds new audit tables and updates user columns before a release.
- Problem
- The team needs a clear summary of what will change in production.
- How to Use
- Paste the current and target DDL, select the database dialect, and inspect the change list plus migration SQL.
- Example Config
-
Schema format: Auto Detect. Dialect: PostgreSQL. - Outcome
- The team gets a concise diff report with table, column, index, and foreign key changes plus a SQL draft.
Try with Samples
sqlRelated Hubs
FAQ
What input formats are supported?
You can provide SQL DDL or JSON/YAML schema summaries. The tool auto-detects the format when possible.
Does it generate migration SQL?
Yes. It produces a draft migration script that can serve as a starting point for review and refinement.
Which databases are targeted?
The tool is designed around MySQL, PostgreSQL, and SQLite style schema changes.
Can it show relationship changes too?
Yes. Foreign key additions and removals are included, along with graph-friendly relation data.