rasinmuhammed/misata

High-performance open-source synthetic data engine. Uses LLMs for schema design and vectorized NumPy for deterministic, scalable generation.

48
/ 100
Emerging

Need to create realistic, interconnected datasets for testing, demos, or simulations? Misata helps you generate complex, multi-table synthetic data by simply describing your business scenario in plain English. It takes your "story" – like "An ecommerce company with seasonal demand" – and outputs structured data tables with consistent relationships, accurate aggregations, and real-world logic. This is ideal for data engineers, QA testers, data scientists, and business analysts who need quality data without using sensitive production information.

Used by 1 other package. Available on PyPI.

Use this if you need to quickly generate realistic, relational test data, demo datasets for dashboards, or simulation scenarios for various business operations, ensuring data integrity across multiple tables.

Not ideal if you're looking for a simple tool to generate disconnected rows of random fake data without any logical relationships or aggregate targets.

data-generation test-data-management database-seeding scenario-simulation BI-dashboard-testing
Maintenance 10 / 25
Adoption 9 / 25
Maturity 22 / 25
Community 7 / 25

How are scores calculated?

Stars

52

Forks

3

Language

Python

License

MIT

Last pushed

Mar 08, 2026

Commits (30d)

0

Dependencies

13

Reverse dependents

1

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