Generate Realistic, Schema-Compliant Synthetic Data

Generate database schemas from natural language descriptions using AI. Describe your tables and relationships, and get production-ready DDL in seconds.

Supports SQL dialects (PostgreSQL, MySQL, Snowflake, Databricks), JSON Schema, XML Schema, and Jinja2 templates. Automatic syntax normalization ensures compatibility.

Import SQL schemas, JSON Schema, XML Schema, or use Jinja2 templates. Generate data that conforms to your types, constraints, nested structures, and relationships.

Support for nested data types including STRUCT and ARRAY (Databricks SQL). Generate realistic hierarchical data with up to 2 levels of nesting.

Generate consistent data across tables with foreign key relationships maintained. No more orphaned records or broken references.

Choose from specialized data generators for emails, phone numbers, credit cards, IP addresses, and much more. Contextually appropriate data.

Drag-and-drop interface to build data generation workflows. Control generation order, set row counts, and configure column overrides.

Integrate data generation directly into your CI/CD pipeline or testing framework with our powerful REST API. Full programmatic access.

Anonymize sensitive data and generate privacy-safe datasets for development and testing without risk. No real data ever used.

Stream generated data directly to your PostgreSQL database. No need to export CSVs and import manually. Supports high-performance bulk inserts.

Generate data by example using Jinja2 templates. Combine static structure with dynamic Faker data for flexible, one-off generation tasks.