🛡️ PRIVACY-SAFE SYNTHETIC DATA

Schema to Dataset

Paste SQL CREATE TABLE schemas (PostgreSQL, MySQL, SQL Server, BigQuery). Our AI reads data types, primary keys, and foreign keys to populate matching records.

How to use: Paste your DDL CREATE TABLE statements below, select target row counts, and generate populated dataset inserts instantly.

Quick Templates

SQL Schema Config

How AI Schema to Dataset Works

✓ Paste one or multiple CREATE TABLE statements for PostgreSQL, MySQL, SQL Server, or BigQuery.

✓ Claude AI reads column semantic names, datatypes, and constraints to generate realistic values.

✓ Primary keys and foreign key relations are strictly mapped with 100% referential integrity.

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Your generated data will appear here

Select your SQL dialect or pick a quick template on the left, paste your CREATE TABLE statements, and click Generate.

🗄️ Multi-Dialect Support

PostgreSQL, MySQL, SQL Server, and BigQuery support with full schema validation.

🧠 AI Relational Mapping

Primary and foreign key relations are parsed and mapped with 100% referential integrity.

📦 Export Formats

Download tables individually as CSV, JSON, SQL, Excel, or all at once.

Paste DDL Script

Enter SQL statements representing your database schemas, tables, and associations.

Analyze Constraints

The parser detects data formats, foreign keys, unique rules, and domain structures automatically.

Get SQL Inserts

Download a populated database dump as SQL INSERT queries ready for immediate execution.

Why Populate Data from Schemas?

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Referential Integrity: Ensures child table rows reference valid parent IDs, matching real database constraints.

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Data Type Matching: Auto-populates dates, integers, text descriptions, and decimals matching column types.

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Mock Complex Models: Effortlessly populate relational setups containing customer profiles, orders, and products.

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100% Offline Seeding: Safely load testing databases without transferring sensitive customer rows outside.

Frequently Asked Questions

Which SQL dialects are supported?

The parser works with standard SQL schemas, including PostgreSQL, MySQL, MS SQL Server, Oracle, SQLite, and Google BigQuery.

How are foreign keys handled?

The tool generates matching primary keys first, and references them in dependent table columns to keep database foreign key constraints valid.

Can I customize the generated values?

Yes. By utilizing logical column naming (e.g. email, full_name, created_at), the AI maps realistic values instead of simple strings.

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