Mock Data Generator
Design schema templates, choose field data types, and instantly generate CSV or JSON datasets. Fully offline, fast, and completely secure.
Schema Definition
Define the fields for your mock data.
Generation Settings
Output
Your generated mock data.
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Streamlined Database Testing
Modern databases and APIs require robust and diverse dataset inputs to simulate edge cases, benchmark query times, and validate input types. Our schema builder supports core data types including UUIDs (RFC-4122 compliant), emails, random integers, booleans, formatted ISO dates, and alphanumeric strings. Designing local mock environments has never been easier or faster.
Enterprise Security & Data Privacy
- Zero Server Logging: No network packets containing your test structures ever traverse the internet.
- Custom Schema Setup: Add, edit, or remove fields dynamically. Set custom keys to match your database field naming conventions.
- Instant Clipboard & File Export: Copy results directly with one click, or trigger a clean, locally compiled file download.
Mock Data Generation Frequently Asked Questions
A Mock Data Generator is a utility used by software developers, database administrators, and QA engineers to create realistic placeholder datasets. It simulates structured production databases, allowing teams to test application logic, API performance, database schemas, and data pipelines without exposing actual user information.
DuckConvert's Mock Data Generator operates 100% locally on your computer. All fields, record counts, and export streams are compiled directly in your web browser session using standard client-side JavaScript. Absolutely zero data is sent to external servers, making it 100% compliant with enterprise security and NDA policies.
You can instantly generate and export mock datasets as structured JSON or Comma-Separated Values (CSV). JSON is perfect for testing Node.js services, NoSQL databases, or front-end REST APIs. CSV is highly compatible with spreadsheet applications like Microsoft Excel, Google Sheets, or relational SQL imports (PostgreSQL, MySQL, SQLite).
Because all generation logic runs on your local processor, the performance is limited only by your browser's allocated memory (RAM). While you can generate thousands of records, we recommend keeping batch runs up to 10,000 rows at a time to ensure instant, fluid browser performance without script lag.