# DATAMIMIC Community Edition 🌟
[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)
[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)
[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)
[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)
[](https://opensource.org/licenses/MIT)
[](https://www.python.org/downloads/)
[](https://github.com/rapiddweller/datamimic/stargazers)
[](https://github.com/rapiddweller/datamimic/network)
[](https://badge.fury.io/py/datamimic-ce)
[](https://pepy.tech/project/datamimic-ce)
---
## Introduction
Welcome to **DATAMIMIC**, the Model-Driven and AI-powered platform that revolutionizes test data generation! By leveraging advanced AI and model-driven technologies, DATAMIMIC enables developers and testers to create realistic, scalable, and privacy-compliant test data with ease.
[](https://www.youtube.com/watch?v=sycO7qd1Bhk)
---
## DATAMIMIC Feature Overview 🎯
### Core Features 🔵
#### 🧠 Model-Driven Generation
- Create sophisticated data models for consistent test data generation
- Define complex relationships between entities
- Support for nested and hierarchical data structures
#### 📊 Data Types & Integration
- **Basic Data Types Support**
- All standard primitive types
- Complex data structures
- Custom data type definitions
- **Core Database Integration**
- RDBMS support (PostgreSQL, MySQL, Oracle)
- MongoDB integration
- Basic import/export functionality
#### 🛡️ Data Privacy & Compliance
- GDPR-compliant data anonymization
- Basic pseudonymization capabilities
- Data masking for sensitive information
- Configurable privacy rules
#### ⚡ Core Capabilities
- **High Performance Engine**
- Optimized for large datasets
- Parallel processing support
- Memory-efficient operations
- **Python Integration**
- Native Python API
- Seamless dependency management
- Python script extensions
- **Basic Extensibility**
- Custom generator support
- Plugin architecture
- Basic scripting capabilities
---
### Enterprise Features 🟣
#### 🧠 AI-Powered Generation
- **GAN-based Synthesis**
- Realistic data patterns
- Learning from existing datasets
- Pattern replication
- **LLM Integration**
- Natural language content
- Context-aware generation
- Semantic consistency
- **Automatic Modeling**
- Schema inference
- Pattern detection
- Model optimization
#### 🔗 Advanced Integrations
- **Streaming Support**
- Kafka integration
- Real-time data generation
- Stream processing
- **Enterprise Formats**
- EDI processing
- Advanced XSD handling
- Custom format support
- **Advanced Connectors**
- Enterprise systems
- Cloud platforms
- Legacy systems
#### 🛡️ Enhanced Privacy Features
- **Advanced Anonymization**
- Context-aware masking
- Reversible anonymization
- Custom privacy rules
- **Compliance Tools**
- Audit logging
- Compliance reporting
- Policy enforcement
- **Enterprise Security**
- Role-based access
- Encryption support
- Security audit trails
#### 📈 Advanced Data Validation
- **Validation Framework**
- Custom rule engines
- Complex validation logic
- Cross-field validation
---
## Why Use DATAMIMIC?
Traditional test data generation can be time-consuming and may compromise data privacy. DATAMIMIC addresses these challenges by:
- **Reducing Time-to-Market**: Quickly generate test data without manual intervention.
- **Enhancing Test Coverage**: Simulate diverse data scenarios for comprehensive testing.
- **Ensuring Compliance**: Maintain data privacy and comply with legal regulations.
- **Improving Data Quality**: Generate realistic data that mirrors production environments.
---
## Installation
### Prerequisites
- **Operating System**: Windows, macOS, or Linux
- **Python**: Version **3.10** or higher
- **Optional**: uv Package Manager for development setup [GitHub](https://github.com/astral-sh/uv)
### User Installation
The simplest way to get started with DATAMIMIC is through pip:
```bash
pip install datamimic-ce
```
Verify the installation:
```bash
datamimic --version
```
### Developer Installation
For contributors and developers who want to work with the source code:
1. Install uv Package Manager:
```bash
pip install uv
```
2. Clone and set up the repository:
```bash
git clone https://github.com/rapiddweller/datamimic.git
cd datamimic
uv sync
```
---
## Usage Guide
### Basic Usage
1. Create a new data generation project:
```bash
datamimic init my-project
cd my-project
```
2. Configure your data model in `datamimic.xml`:
```xml
<setup>
<generate name="datamimic_user_list" count="100" target="CSV,JSON">
<variable name="person" entity="Person(min_age=18, max_age=90, female_quota=0.5)"/>
<key name="id" generator="IncrementGenerator"/>
<key name="first_name" script="person.given_name"/>
<key name="last_name" script="person.family_name"/>
<key name="gender" script="person.gender"/>
<key name="birth_date" script="person.birthdate" converter="DateFormat('%d.%m.%Y')"/>
<key name="email" script="person.family_name + '@' + person.given_name + '.de'"/>
<key name="ce_user" values="True, False"/>
<key name="ee_user" values="True, False"/>
<key name="datamimic_lover" constant="DEFINITELY"/>
</generate>
</setup>
```
3. Generate data:
```bash
datamimic run datamimic.xml
```
4. Access the generated data in the `output` directory.
**json export:**
```json
[
{"id": 1, "first_name": "Mary", "last_name": "Mcgowan", "gender": "female", "birth_date": "1946-05-15T00:00:00", "email": "Mcgowan@Mary.de", "ce_user": false, "ee_user": true, "datamimic_lover": "DEFINITELY"},
{"id": 2, "first_name": "Gabrielle", "last_name": "Malone", "gender": "female", "birth_date": "1989-11-27T00:00:00", "email": "Malone@Gabrielle.de", "ce_user": false, "ee_user": true, "datamimic_lover": "DEFINITELY"},
{"id": 4, "first_name": "Margaret", "last_name": "Torres", "gender": "female", "birth_date": "2006-07-13T00:00:00", "email": "Torres@Margaret.de", "ce_user": false, "ee_user": false, "datamimic_lover": "DEFINITELY"},
{"id": 5, "first_name": "Monica", "last_name": "Meyers", "gender": "female", "birth_date": "1983-07-22T00:00:00", "email": "Meyers@Monica.de", "ce_user": true, "ee_user": false, "datamimic_lover": "DEFINITELY"},
{"id": 6, "first_name": "Jason", "last_name": "Davis", "gender": "male", "birth_date": "1941-07-05T00:00:00", "email": "Davis@Jason.de", "ce_user": true, "ee_user": false, "datamimic_lover": "DEFINITELY"},
{"...": "..."},
{"id": 100, "first_name": "Jared", "last_name": "Rivas", "gender": "male", "birth_date": "1975-03-16T00:00:00", "email": "Rivas@Jared.de", "ce_user": true, "ee_user": true, "datamimic_lover": "DEFINITELY"}
]
```
**csv export:**
```csv
id|first_name|last_name|gender|birth_date|email|ce_user|ee_user|datamimic_lover
1|Mary|Mcgowan|female|1946-05-15 00:00:00|Mcgowan@Mary.de|False|True|DEFINITELY
2|Gabrielle|Malone|female|1989-11-27 00:00:00|Malone@Gabrielle.de|False|True|DEFINITELY
3|Antonio|Davis|male|2005-05-12 00:00:00|Davis@Antonio.de|False|True|DEFINITELY
4|Margaret|Torres|female|2006-07-13 00:00:00|Torres@Margaret.de|False|False|DEFINITELY
5|Monica|Meyers|female|1983-07-22 00:00:00|Meyers@Monica.de|True|False|DEFINITELY
...
100|Jason|Davis|male|1941-07-05 00:00:00|Davis@Jason.de|True|False|DEFINITELY
```
### Advanced Features
DATAMIMIC supports various advanced features:
- **Custom Generators**: Create your own data generators
- **Data Relationships**: Define complex relationships between entities
- **Import/Export Formats**: Support for JSON, XML, CSV, RDBMS and MongoDB
- **Import/Export Formats ( only EE )**: Kafka, EDI, XSD and more
- **Data Anonymization**: Anonymize data to comply with privacy regulations
- **Data Validation**: Define and enforce data validation rules
- **Scripting**: Extend functionality using Python scripts
- **Database Integration**: Connect to databases for seamless data generation
- **Model-Driven Generation**: Utilize models to generate realistic data
- **Validation Rules**: Define and enforce data validation rules
- **Scripting**: Extend functionality using Python scripts
---
## Examples and Demos
Explore our demo collection:
```bash
# List available demos
datamimic demo list
# Run a specific demo
datamimic demo create demo-model
datamimic run ./demo-model/datamimic.xml
```
Key demos include:
- Basic entity generation
- Complex relationships
- Database integration
- Custom generator creation
- Privacy compliance examples
Find more examples in the `datamimic_ce/demos` directory.
---
## Contributing
We ❤️ contributions! Here's how you can help:
- **Code Contributions**: Submit pull requests for new features or bug fixes.
- **Documentation**: Improve existing docs or help with translations.
- **Community Engagement**: Join discussions and support other users.
---
## 📜 DATAMIMIC Licensing Options
### 🌟 Community Edition
Open Source Freedom for Everyone
#### ✨ Key Benefits
- **🔓 MIT License**: Maximum freedom for innovation
- **💼 Commercial Ready**: Use freely in commercial projects
- **🔄 Modification Rights**: Full source code access and modification rights
- **🌍 No Restrictions**: Deploy anywhere, anytime
#### 🎁 What's Included
- **📦 Core Features**
- Model-driven data generation
- Basic data types & integrations
- GDPR compliance tools
- **👥 Community Support**
- Active GitHub community
- Public issue tracking
- Community discussions
- Regular updates
#### 💫 Perfect For
- Individual developers
- Startups & small teams
- Open source projects
- Learning & evaluation
- POC development
---
### ⭐ Enterprise Edition
Professional Power for Business Success
#### 🚀 Premium Benefits
- **📋 Commercial License**: Enterprise-grade flexibility
- **🔐 Advanced Features**: Full suite of professional tools
- **🎯 Priority Support**: Direct access to expert team
- **🛠️ Custom Solutions**: Tailored to your needs
#### 💎 Premium Features
- **🤖 AI Capabilities**
- GAN-based synthesis
- LLM integration
- Automated modeling
- **🔗 Enterprise Integration**
- Advanced connectors
- Kafka streaming
- EDI support
- **🛡️ Enhanced Security**
- Advanced privacy features
- Compliance reporting
- Audit trails
#### 🎯 Ideal For
- Large enterprises
- Financial institutions
- Healthcare organizations
- Government agencies
- High-compliance industries
#### 📞 Get Started
>
> Ready to unlock the full potential of DATAMIMIC?
**Contact Our Team:**
- 📧 Email: [sales@rapiddweller.com](mailto:sales@rapiddweller.com)
- 🌐 Visit: [datamimic.io/enterprise](https://datamimic.io)
---
### 🤝 Compare Editions
| Feature | Community | Enterprise |
|---------|-----------|------------|
| Base Features | ✅ | ✅ |
| Source Code Access | ✅ | ✅ |
| Commercial Use | ✅ | ✅ |
| AI Features | ❌ | ✅ |
| Priority Support | ❌ | ✅ |
| Enterprise Integrations | ❌ | ✅ |
| SLA Support | ❌ | ✅ |
| Custom Development | ❌ | ✅ |
---
> ***"Empower your data generation journey with the right DATAMIMIC edition for your needs"***
---
## Support
Need help or have questions? We're here for you!
- 📚 [Documentation](https://docs.datamimic.io)
- 💬 [GitHub Discussions](https://github.com/rapiddweller/datamimic/discussions)
- 🐛 [Issue Tracker](https://github.com/rapiddweller/datamimic/issues)
- 📧 [Email Support](mailto:support@rapiddweller.com)
---
## Connect with Us
Stay updated and connect with our community!
- 🌐 **Website**: [www.datamimic.io](https://datamimic.io)
- 🏢 **Rapiddweller**: [www.rapiddweller.com](https://rapiddweller.com)
- 💼 **LinkedIn**: [rapiddweller](https://www.linkedin.com/company/rapiddweller)
---
## Acknowledgments
A big thank you to all our contributors! Your efforts make DATAMIMIC possible.
---
**Don't forget to ⭐ star and 👀 watch this repository to stay updated!**
---
## Legal Notices
For detailed licensing information, please see the [LICENSE](LICENSE) file.
Raw data
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"description": "# DATAMIMIC Community Edition \ud83c\udf1f\n\n[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)\n[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)\n[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)\n[](https://sonarcloud.io/summary/new_code?id=rapiddweller_datamimic)\n[](https://opensource.org/licenses/MIT)\n[](https://www.python.org/downloads/)\n[](https://github.com/rapiddweller/datamimic/stargazers)\n[](https://github.com/rapiddweller/datamimic/network)\n[](https://badge.fury.io/py/datamimic-ce)\n[](https://pepy.tech/project/datamimic-ce)\n---\n\n## Introduction\n\nWelcome to **DATAMIMIC**, the Model-Driven and AI-powered platform that revolutionizes test data generation! By leveraging advanced AI and model-driven technologies, DATAMIMIC enables developers and testers to create realistic, scalable, and privacy-compliant test data with ease.\n\n[](https://www.youtube.com/watch?v=sycO7qd1Bhk)\n\n---\n\n## DATAMIMIC Feature Overview \ud83c\udfaf\n\n### Core Features \ud83d\udd35\n\n#### \ud83e\udde0 Model-Driven Generation\n\n- Create sophisticated data models for consistent test data generation\n- Define complex relationships between entities\n- Support for nested and hierarchical data structures\n\n#### \ud83d\udcca Data Types & Integration\n\n- **Basic Data Types Support**\n - All standard primitive types\n - Complex data structures\n - Custom data type definitions\n- **Core Database Integration**\n - RDBMS support (PostgreSQL, MySQL, Oracle)\n - MongoDB integration\n - Basic import/export functionality\n\n#### \ud83d\udee1\ufe0f Data Privacy & Compliance\n\n- GDPR-compliant data anonymization\n- Basic pseudonymization capabilities\n- Data masking for sensitive information\n- Configurable privacy rules\n\n#### \u26a1 Core Capabilities\n\n- **High Performance Engine**\n - Optimized for large datasets\n - Parallel processing support\n - Memory-efficient operations\n- **Python Integration**\n - Native Python API\n - Seamless dependency management\n - Python script extensions\n- **Basic Extensibility**\n - Custom generator support\n - Plugin architecture\n - Basic scripting capabilities\n\n---\n\n### Enterprise Features \ud83d\udfe3\n\n#### \ud83e\udde0 AI-Powered Generation\n\n- **GAN-based Synthesis**\n - Realistic data patterns\n - Learning from existing datasets\n - Pattern replication\n- **LLM Integration**\n - Natural language content\n - Context-aware generation\n - Semantic consistency\n- **Automatic Modeling**\n - Schema inference\n - Pattern detection\n - Model optimization\n\n#### \ud83d\udd17 Advanced Integrations\n\n- **Streaming Support**\n - Kafka integration\n - Real-time data generation\n - Stream processing\n- **Enterprise Formats**\n - EDI processing\n - Advanced XSD handling\n - Custom format support\n- **Advanced Connectors**\n - Enterprise systems\n - Cloud platforms\n - Legacy systems\n\n#### \ud83d\udee1\ufe0f Enhanced Privacy Features\n\n- **Advanced Anonymization**\n - Context-aware masking\n - Reversible anonymization\n - Custom privacy rules\n- **Compliance Tools**\n - Audit logging\n - Compliance reporting\n - Policy enforcement\n- **Enterprise Security**\n - Role-based access\n - Encryption support\n - Security audit trails\n\n#### \ud83d\udcc8 Advanced Data Validation\n\n- **Validation Framework**\n - Custom rule engines\n - Complex validation logic\n - Cross-field validation\n\n---\n\n## Why Use DATAMIMIC?\n\nTraditional test data generation can be time-consuming and may compromise data privacy. DATAMIMIC addresses these challenges by:\n\n- **Reducing Time-to-Market**: Quickly generate test data without manual intervention.\n- **Enhancing Test Coverage**: Simulate diverse data scenarios for comprehensive testing.\n- **Ensuring Compliance**: Maintain data privacy and comply with legal regulations.\n- **Improving Data Quality**: Generate realistic data that mirrors production environments.\n\n---\n\n## Installation\n\n### Prerequisites\n\n- **Operating System**: Windows, macOS, or Linux\n- **Python**: Version **3.10** or higher\n- **Optional**: uv Package Manager for development setup [GitHub](https://github.com/astral-sh/uv)\n\n### User Installation\n\nThe simplest way to get started with DATAMIMIC is through pip:\n\n```bash\npip install datamimic-ce\n```\n\nVerify the installation:\n\n```bash\ndatamimic --version\n```\n\n### Developer Installation\n\nFor contributors and developers who want to work with the source code:\n\n1. Install uv Package Manager:\n\n ```bash\n pip install uv\n ```\n\n2. Clone and set up the repository:\n\n ```bash\n git clone https://github.com/rapiddweller/datamimic.git\n cd datamimic\n uv sync\n ```\n\n---\n\n## Usage Guide\n\n### Basic Usage\n\n1. Create a new data generation project:\n\n ```bash\n datamimic init my-project\n cd my-project\n ```\n\n2. Configure your data model in `datamimic.xml`:\n\n ```xml\n <setup>\n <generate name=\"datamimic_user_list\" count=\"100\" target=\"CSV,JSON\">\n <variable name=\"person\" entity=\"Person(min_age=18, max_age=90, female_quota=0.5)\"/>\n <key name=\"id\" generator=\"IncrementGenerator\"/>\n <key name=\"first_name\" script=\"person.given_name\"/>\n <key name=\"last_name\" script=\"person.family_name\"/>\n <key name=\"gender\" script=\"person.gender\"/>\n <key name=\"birth_date\" script=\"person.birthdate\" converter=\"DateFormat('%d.%m.%Y')\"/>\n <key name=\"email\" script=\"person.family_name + '@' + person.given_name + '.de'\"/>\n <key name=\"ce_user\" values=\"True, False\"/>\n <key name=\"ee_user\" values=\"True, False\"/>\n <key name=\"datamimic_lover\" constant=\"DEFINITELY\"/>\n </generate>\n </setup>\n ```\n\n3. Generate data:\n\n ```bash\n datamimic run datamimic.xml\n ```\n\n4. Access the generated data in the `output` directory.\n\n **json export:**\n\n ```json\n [\n {\"id\": 1, \"first_name\": \"Mary\", \"last_name\": \"Mcgowan\", \"gender\": \"female\", \"birth_date\": \"1946-05-15T00:00:00\", \"email\": \"Mcgowan@Mary.de\", \"ce_user\": false, \"ee_user\": true, \"datamimic_lover\": \"DEFINITELY\"},\n {\"id\": 2, \"first_name\": \"Gabrielle\", \"last_name\": \"Malone\", \"gender\": \"female\", \"birth_date\": \"1989-11-27T00:00:00\", \"email\": \"Malone@Gabrielle.de\", \"ce_user\": false, \"ee_user\": true, \"datamimic_lover\": \"DEFINITELY\"},\n {\"id\": 4, \"first_name\": \"Margaret\", \"last_name\": \"Torres\", \"gender\": \"female\", \"birth_date\": \"2006-07-13T00:00:00\", \"email\": \"Torres@Margaret.de\", \"ce_user\": false, \"ee_user\": false, \"datamimic_lover\": \"DEFINITELY\"},\n {\"id\": 5, \"first_name\": \"Monica\", \"last_name\": \"Meyers\", \"gender\": \"female\", \"birth_date\": \"1983-07-22T00:00:00\", \"email\": \"Meyers@Monica.de\", \"ce_user\": true, \"ee_user\": false, \"datamimic_lover\": \"DEFINITELY\"},\n {\"id\": 6, \"first_name\": \"Jason\", \"last_name\": \"Davis\", \"gender\": \"male\", \"birth_date\": \"1941-07-05T00:00:00\", \"email\": \"Davis@Jason.de\", \"ce_user\": true, \"ee_user\": false, \"datamimic_lover\": \"DEFINITELY\"},\n {\"...\": \"...\"},\n {\"id\": 100, \"first_name\": \"Jared\", \"last_name\": \"Rivas\", \"gender\": \"male\", \"birth_date\": \"1975-03-16T00:00:00\", \"email\": \"Rivas@Jared.de\", \"ce_user\": true, \"ee_user\": true, \"datamimic_lover\": \"DEFINITELY\"}\n ]\n ```\n\n **csv export:**\n\n ```csv\n id|first_name|last_name|gender|birth_date|email|ce_user|ee_user|datamimic_lover\n 1|Mary|Mcgowan|female|1946-05-15 00:00:00|Mcgowan@Mary.de|False|True|DEFINITELY\n 2|Gabrielle|Malone|female|1989-11-27 00:00:00|Malone@Gabrielle.de|False|True|DEFINITELY\n 3|Antonio|Davis|male|2005-05-12 00:00:00|Davis@Antonio.de|False|True|DEFINITELY\n 4|Margaret|Torres|female|2006-07-13 00:00:00|Torres@Margaret.de|False|False|DEFINITELY\n 5|Monica|Meyers|female|1983-07-22 00:00:00|Meyers@Monica.de|True|False|DEFINITELY\n ...\n 100|Jason|Davis|male|1941-07-05 00:00:00|Davis@Jason.de|True|False|DEFINITELY\n ```\n\n### Advanced Features\n\nDATAMIMIC supports various advanced features:\n\n- **Custom Generators**: Create your own data generators\n- **Data Relationships**: Define complex relationships between entities\n- **Import/Export Formats**: Support for JSON, XML, CSV, RDBMS and MongoDB\n- **Import/Export Formats ( only EE )**: Kafka, EDI, XSD and more\n- **Data Anonymization**: Anonymize data to comply with privacy regulations\n- **Data Validation**: Define and enforce data validation rules\n- **Scripting**: Extend functionality using Python scripts\n- **Database Integration**: Connect to databases for seamless data generation\n- **Model-Driven Generation**: Utilize models to generate realistic data\n- **Validation Rules**: Define and enforce data validation rules\n- **Scripting**: Extend functionality using Python scripts\n\n---\n\n## Examples and Demos\n\nExplore our demo collection:\n\n```bash\n# List available demos\ndatamimic demo list\n\n# Run a specific demo\ndatamimic demo create demo-model\ndatamimic run ./demo-model/datamimic.xml\n```\n\nKey demos include:\n\n- Basic entity generation\n- Complex relationships\n- Database integration\n- Custom generator creation\n- Privacy compliance examples\n\nFind more examples in the `datamimic_ce/demos` directory.\n\n---\n\n## Contributing\n\nWe \u2764\ufe0f contributions! Here's how you can help:\n\n- **Code Contributions**: Submit pull requests for new features or bug fixes.\n- **Documentation**: Improve existing docs or help with translations.\n- **Community Engagement**: Join discussions and support other users.\n\n---\n\n## \ud83d\udcdc DATAMIMIC Licensing Options\n\n### \ud83c\udf1f Community Edition\n\nOpen Source Freedom for Everyone\n\n#### \u2728 Key Benefits\n\n- **\ud83d\udd13 MIT License**: Maximum freedom for innovation\n- **\ud83d\udcbc Commercial Ready**: Use freely in commercial projects\n- **\ud83d\udd04 Modification Rights**: Full source code access and modification rights\n- **\ud83c\udf0d No Restrictions**: Deploy anywhere, anytime\n\n#### \ud83c\udf81 What's Included\n\n- **\ud83d\udce6 Core Features**\n - Model-driven data generation\n - Basic data types & integrations\n - GDPR compliance tools\n \n- **\ud83d\udc65 Community Support**\n - Active GitHub community\n - Public issue tracking\n - Community discussions\n - Regular updates\n\n#### \ud83d\udcab Perfect For\n\n- Individual developers\n- Startups & small teams\n- Open source projects\n- Learning & evaluation\n- POC development\n\n---\n\n### \u2b50 Enterprise Edition\n\nProfessional Power for Business Success\n\n#### \ud83d\ude80 Premium Benefits\n\n- **\ud83d\udccb Commercial License**: Enterprise-grade flexibility\n- **\ud83d\udd10 Advanced Features**: Full suite of professional tools\n- **\ud83c\udfaf Priority Support**: Direct access to expert team\n- **\ud83d\udee0\ufe0f Custom Solutions**: Tailored to your needs\n\n#### \ud83d\udc8e Premium Features\n\n- **\ud83e\udd16 AI Capabilities**\n - GAN-based synthesis\n - LLM integration\n - Automated modeling\n \n- **\ud83d\udd17 Enterprise Integration**\n - Advanced connectors\n - Kafka streaming\n - EDI support\n \n- **\ud83d\udee1\ufe0f Enhanced Security**\n - Advanced privacy features\n - Compliance reporting\n - Audit trails\n\n#### \ud83c\udfaf Ideal For\n\n- Large enterprises\n- Financial institutions\n- Healthcare organizations\n- Government agencies\n- High-compliance industries\n\n#### \ud83d\udcde Get Started\n>\n> Ready to unlock the full potential of DATAMIMIC?\n\n**Contact Our Team:**\n\n- \ud83d\udce7 Email: [sales@rapiddweller.com](mailto:sales@rapiddweller.com)\n- \ud83c\udf10 Visit: [datamimic.io/enterprise](https://datamimic.io)\n\n---\n\n### \ud83e\udd1d Compare Editions\n\n| Feature | Community | Enterprise |\n|---------|-----------|------------|\n| Base Features | \u2705 | \u2705 |\n| Source Code Access | \u2705 | \u2705 |\n| Commercial Use | \u2705 | \u2705 |\n| AI Features | \u274c | \u2705 |\n| Priority Support | \u274c | \u2705 |\n| Enterprise Integrations | \u274c | \u2705 |\n| SLA Support | \u274c | \u2705 |\n| Custom Development | \u274c | \u2705 |\n\n---\n\n> ***\"Empower your data generation journey with the right DATAMIMIC edition for your needs\"***\n\n---\n\n## Support\n\nNeed help or have questions? We're here for you!\n\n- \ud83d\udcda [Documentation](https://docs.datamimic.io)\n- \ud83d\udcac [GitHub Discussions](https://github.com/rapiddweller/datamimic/discussions)\n- \ud83d\udc1b [Issue Tracker](https://github.com/rapiddweller/datamimic/issues)\n- \ud83d\udce7 [Email Support](mailto:support@rapiddweller.com)\n\n---\n\n## Connect with Us\n\nStay updated and connect with our community!\n\n- \ud83c\udf10 **Website**: [www.datamimic.io](https://datamimic.io)\n- \ud83c\udfe2 **Rapiddweller**: [www.rapiddweller.com](https://rapiddweller.com)\n- \ud83d\udcbc **LinkedIn**: [rapiddweller](https://www.linkedin.com/company/rapiddweller)\n\n---\n\n## Acknowledgments\n\nA big thank you to all our contributors! Your efforts make DATAMIMIC possible.\n\n---\n\n**Don't forget to \u2b50 star and \ud83d\udc40 watch this repository to stay updated!**\n\n---\n\n## Legal Notices\n\nFor detailed licensing information, please see the [LICENSE](LICENSE) file.\n",
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