Create custom fake data for testing and development. Build realistic test datasets with our flexible field editor.
A fake data generator is an indispensable tool for developers, testers, and data analysts who need realistic sample data without using real personal information. Whether you're building a new application, testing database queries, creating API mock responses, or setting up development environments, generating fake data saves countless hours of manual data entry while ensuring privacy compliance.
Our free fake data generator provides a flexible, user-friendly interface that allows you to create custom datasets tailored to your specific needs. Unlike rigid templates that force you into predefined structures, our tool functions as a dynamic editor where you can add, remove, and configure fields exactly as your project requires. This flexibility makes it perfect for everything from simple user profiles to complex nested data structures.
Traditional approaches to generating test data often involve manual creation, which is time-consuming and error-prone, or using fixed templates that don't match your actual data schema. Our generator solves both problems by providing a customizable field editor that puts you in complete control. You decide what fields to include, what type of data each field should contain, and how many records to generate—up to 500 entries per batch.
The tool generates realistic, varied data that mimics real-world patterns. Names follow common naming conventions, email addresses use proper formatting, phone numbers include valid area codes, and addresses combine realistic street names with actual cities and countries. This realism is crucial for meaningful testing, as it helps identify issues that might only appear with realistic data patterns.
Our field editor allows you to build custom data structures from scratch. Add as many fields as you need, name them according to your schema, and select the appropriate data type for each. Remove fields you don't need with a single click, and rearrange your data structure to match your application's requirements exactly.
Choose from a comprehensive selection of data types designed to cover most common use cases:
Many data types support additional configuration to fine-tune the generated values. For numeric fields, set minimum and maximum values to control the range. For text fields, specify the desired length. For dates, define start and end dates to generate values within a specific timeframe. These options ensure the generated data matches your testing requirements precisely.
All generated data is output in clean, formatted JSON that's ready to use in your applications, APIs, or databases. The JSON structure matches your field configuration exactly, making it easy to import into your development environment or use directly in API testing tools like Postman or Insomnia.
During application development, you need test data to verify functionality, test edge cases, and ensure your application handles various data scenarios correctly. Our generator helps you quickly create datasets that cover different scenarios—from minimal records to large datasets of 500 entries. This is especially valuable when developing features that depend on data relationships or when testing pagination, filtering, and sorting functionality.
Database developers and administrators use fake data generators to populate test databases with realistic sample data. This allows them to test queries, indexes, and database performance without exposing real user information. The ability to generate hundreds of records quickly makes it ideal for stress testing and performance benchmarking.
API developers frequently need sample responses for documentation, testing, and client development. Our generator creates JSON data that matches your API's expected structure, making it perfect for creating mock API responses. Frontend developers can use this data to build and test user interfaces before backend APIs are ready, accelerating the development process.
Designers and frontend developers need realistic data to see how interfaces look and behave with actual content. Fake data generators help create datasets that demonstrate how tables, lists, cards, and other UI components handle various data lengths, formats, and edge cases. This is crucial for responsive design testing and ensuring interfaces work well with different content scenarios.
When creating training materials, documentation, or tutorials, you often need sample data that demonstrates concepts without using real information. Our generator creates realistic examples that help learners understand data structures and relationships without privacy concerns.
Before generating data, review your actual database schema or API structure. Use the same field names and data types in the generator to ensure compatibility. This prevents import errors and ensures the generated data works seamlessly with your application.
When configuring numeric fields, use realistic min/max values that match your application's expected data ranges. For example, if generating ages, use 18-100 rather than 0-1000. Realistic ranges help identify issues that might occur with actual user data.
Generate multiple datasets with different configurations to test edge cases. Create datasets with minimal fields, maximum fields, very long text values, and boundary numeric values. This comprehensive testing helps ensure your application handles various data scenarios correctly.
After generating data, quickly review a few records to ensure they match your expectations. Check that email addresses are properly formatted, phone numbers follow expected patterns, and numeric values fall within expected ranges. This validation catches configuration errors early.
Start with small datasets (5-10 records) to verify your configuration, then generate larger batches as needed. For performance testing, generate the maximum 500 records. For UI testing, smaller datasets often suffice and are easier to review.
Full Name: Generates realistic first and last name combinations from common names. First Name: Generates only first names. Last Name: Generates only last names. Email: Creates properly formatted email addresses using generated names and random domains. Phone: Generates phone numbers in standard format with area codes.
Full Address: Combines street address, city, country, and zip code into a complete address string. City: Generates city names from a list of major cities. Country: Selects from a list of countries. Zip Code: Generates 5-digit zip codes.
Number: Generates decimal numbers within your specified min/max range. Useful for prices, measurements, or any decimal values. Integer: Generates whole numbers within your specified range. Perfect for counts, IDs, or age values.
Text: Generates random alphanumeric strings of specified length. Useful for generating IDs, codes, or random text values. Custom Value: Allows you to specify exact values or patterns. Useful for fields that need specific values or when you want to test with known data.
Date: Generates dates within a specified range. Configure start and end dates in YYYY-MM-DD format. Perfect for birth dates, registration dates, or any date fields in your schema.
Boolean: Generates random true/false values. Useful for flags, status fields, or yes/no fields. UUID: Generates standard UUID v4 identifiers. Perfect for unique identifiers in distributed systems. URL: Generates random web addresses. Useful for testing link handling or URL validation.
One of the primary advantages of using fake data generators is privacy protection. By generating synthetic data instead of using real user information, you eliminate privacy risks and comply with data protection regulations like GDPR and CCPA. This is especially important during development and testing phases where data might be shared, logged, or exposed in ways that wouldn't be acceptable with real user data.
Our generator processes all data generation client-side in your browser. We don't store, transmit, or log any of your field configurations or generated data. Your data never leaves your device, ensuring complete privacy and security. This client-side processing also means the tool works offline after initial page load and doesn't require internet connectivity for data generation.
The JSON output format makes integration straightforward. You can copy generated data directly into JSON files for import into databases, paste it into API testing tools, use it in unit tests, or integrate it into seed scripts for database initialization. Many developers use our generator to create initial datasets for new projects or to refresh test databases with new sample data.
For automated testing workflows, you can generate data, save it to files, and use it in your test suites. The consistent structure makes it easy to write tests that expect specific data formats, while the randomness ensures tests cover various data scenarios.
You can generate up to 500 records per batch. This limit balances performance with practical needs. For larger datasets, simply generate multiple batches and combine them if needed.
Currently, field configurations are session-based and reset when you refresh the page. However, you can quickly recreate configurations, and the flexible editor makes it easy to build new structures. Consider bookmarking common configurations or keeping notes on your preferred field setups.
Yes, each generation creates new random values. Names, emails, addresses, and other values are randomly selected from pools of realistic options, ensuring variety in your datasets. This randomness is important for comprehensive testing.
The current version generates flat JSON objects. For nested structures, you can generate separate datasets and manually combine them, or use the custom value type to create JSON strings that you can parse. Future enhancements may include direct support for nested objects.
Yes, after the initial page load, all data generation happens client-side in your browser. You don't need an internet connection to generate data, making it perfect for development environments with limited connectivity.
Our free fake data generator provides a powerful, flexible solution for creating test data that matches your exact requirements. The customizable field editor puts you in control, allowing you to build data structures that perfectly match your application's schema. With 17+ data types, support for up to 500 records, and complete privacy through client-side processing, it's an essential tool for modern development workflows.
Whether you're a developer building new features, a tester creating test cases, a designer prototyping interfaces, or a data analyst setting up test environments, our generator helps you work faster and more efficiently. Start generating your custom test data today and experience the difference that realistic, properly structured fake data makes in your development process.