DATAMIMIC is an AI-powered, model-driven test data generation platform designed to quickly deliver realistic, privacy-compliant synthetic data.
✅ Model-driven | ✅ AI-ready | ✅ Privacy-focused | ✅ Open Source (MIT)
📞 Book your Free Strategy Call and Demo to explore the full power of our Enterprise solution!
| Feature | Community | Enterprise |
|---|---|---|
| Core Model-driven Generation | ✅ | ✅ |
| Python & XML APIs | ✅ | ✅ |
| Basic Anonymization | ✅ | ✅ |
| AI-Enhanced Data Generation | ❌ | ✅ |
| Advanced Enterprise Integrations | ❌ | ✅ |
| Priority Support & SLA | ❌ | ✅ |
👉 Learn more about Enterprise Edition
Install easily via pip:
pip install datamimic-ceVerify installation:
datamimic versionGenerate realistic data effortlessly:
Python Example:
from datamimic_ce.domains.common.services import PersonService
person_service = PersonService(dataset="US")
person = person_service.generate()
print(f"Person: {person.name}, Email: {person.email}")XML Example:
<setup>
<generate name="user_data" count="10" target="CSV">
<key name="name" entity="Person().name"/>
<key name="email" entity="Person().email"/>
</generate>
</setup>Run XML via CLI:
datamimic run datamimic.xmlQuickly generate test-specific data using DataMimicTestFactory:
customer.xml:
<setup>
<generate name="customer" count="10">
<variable name="person" entity="Person(min_age=21, max_age=67)"/>
<key name="id" generator="IncrementGenerator"/>
<key name="first_name" script="person.given_name"/>
<key name="last_name" script="person.family_name"/>
<key name="email" script="person.email"/>
<key name="status" values="'active', 'inactive', 'pending'"/>
</generate>
</setup>Python Usage:
from datamimic_ce.factory.datamimic_test_factory import DataMimicTestFactory
customer_factory = DataMimicTestFactory("customer.xml", "customer")
customer = customer_factory.create()
print(customer["id"]) # 1
print(customer["first_name"]) # Jose
print(customer["last_name"]) # Ayers- 🚀 Accelerate Development: Instantly create test data.
- 🛡️ Privacy First: Built-in GDPR compliance.
- 📊 Realistic Data: Authentic, weighted distributions from various data domains.
- 🔧 High Flexibility: Easily model, standardize, and customize data generation processes.
- 📥📤 Versatile Sources: Extensive import/export capabilities (JSON, XML, CSV, RDBMS, MongoDB, etc.).
- 🗃️ Metadata-Driven: Operate seamlessly with an integrated metadata model.
- 📚 Full Documentation
- 🚀 Run an instant demo:
datamimic demo create healthcare-example
datamimic run ./healthcare-example/datamimic.xmlQ: Is Community Edition suitable for commercial projects?
A: Absolutely! DATAMIMIC CE uses the MIT License.
Q: Why upgrade to Enterprise Edition (EE) instead of using Community Edition (CE)?
A: EE provides a web UI, enterprise support, team collaboration, and advanced features like AI-powered test data generation, workflow automation, and compliance tools.
Q: Can I contribute?
A: Yes! See Contributing Guide.
⭐ Star us on GitHub to keep DATAMIMIC growing!