🗄️ BETA · SYLVAERA

Schema → Dataset

Paste your SQL schema — get realistic, relationally consistent test data instantly respecting your foreign keys.

SQL Config
How to use Schema to Dataset
✓ Paste one or multiple CREATE TABLE statements.
✓ Foreign key relations (references) will be automatically detected and respected.
✓ Data types (VARCHAR, INT, DATE, etc.) and constraints are automatically inferred.
🗄️

Your generated data will appear here

Select your SQL dialect, paste your CREATE TABLE statements on the left, and click Generate.

🗄️ Schema Support
PostgreSQL, MySQL, and T-SQL support. Parse multiple tables.
📊 Smart Mapping
Primary and foreign key relations are parsed and mapped accurately.
📦 Export Formats
Download tables individually as CSV/JSON or all at once in Excel.

Generate Relational Test Data Directly from SQL Schemas

When building apps, developers need rich test datasets that resemble production data. Creating mock data manually is tedious, and writing custom seeding scripts is error-prone. The **Schema to Dataset** tool parses your raw SQL statements, resolves relations, and outputs consistent tables automatically.

How the Generator Works

1

Paste SQL

Copy and paste your CREATE TABLE statements directly into the code editor.

2

Select Rows

Configure how many records you need (up to 10,000 rows per generation).

3

Download

Preview your tables, select individual files, or grab a multi-sheet Excel workbook.

Frequently Asked Questions

Are foreign key dependencies maintained?

Yes. The generator parses references and checks target primary keys. For example, order records are generated referencing valid user IDs automatically.

Is my SQL schema stored on your servers?

No. All SQL parsing and data generation run temporarily. Once your session ends, the records are completely deleted from our memory cache. No logs or schemas are persisted.

Can I generate more than 10,000 rows?

To maintain fast load times and keep this tool completely free, a single run is limited to 10,000 rows. You can execute multiple generations for larger sets.