RanGen
RanGen is an open-source, desktop software for generating random data such as names, addresses, social security numbers, etc. for testing databases and applications. It is lightweight, customizable, and offers useful features for data modeling and testing.
testing
random-data
data-modeling
RanGen: Open-Source Desktop Random Data Generator
Open-source desktop software for generating random data, ideal for testing databases and applications.
What is RanGen?
RanGen is an open source, cross-platform desktop application for generating random test data including names, addresses, social security numbers, credit card numbers, etc. It provides data developers and testers an easy way to populate databases, APIs, and applications with large volumes of realistic fake data for development, testing, and training purposes.
Some key features of RanGen include:
- Lightweight desktop application with an intuitive and responsive UI
- Generates random data for names, addresses, phone numbers, email, credit cards, etc. from various countries and locales
- Output data types include SQL, JSON, CSV, and Excel
- Customizable data models and generation rules
- Repeated data detection for identifying duplicate records
- Data scrambling for privacy
- Command line access for easy automation and integration
With its flexibility, customization options, small footprint, and open source code base, RanGen makes an excellent choice of tool for software teams and QAs looking to mocking up and testing data-driven systems with large volumes of randomized test data under different constraints and use cases.
RanGen Features
Features
- Generate random data for names, addresses, phone numbers, email addresses, social security numbers, credit card numbers, etc.
- Customize data fields and formats
- Export generated data to CSV, JSON, SQL, etc.
- Lightweight and fast
- Open source and free
Pricing
- Open Source
- Free
Pros
Free and open source
Easy to use with intuitive interface
Highly customizable and flexible
Lightweight with minimal system resource usage
Exports data to various formats
Cons
Limited to random data generation
Not suitable for complex data modeling
Lacks some advanced or niche data types
Basic interface without many bells and whistles
Official Links
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