Fake Data Generator

Generate realistic test data for development and testing. No row limits, no signup, 100% browser-based.

🔒 100% Client-Side No Row Limits 🌐 Locale-Aware Data 💾 Save & Load Schemas
Schema Builder 0 fields
Column Name Data Type Null%
{...}
No data generated yet
Add fields to your schema, choose a preset, or import a saved schema. Then click Generate Data.

How to Use This Fake Data Generator

This tool generates realistic fake data entirely in your browser. Nothing is sent to any server, so your schemas and generated data stay completely private. Here's how to get started:

1. Choose a locale. Select the country or language that best matches the data you need. The generator will produce names, addresses, phone numbers, and other locale-specific data that are internally consistent. A Japanese locale generates Japanese names with Japanese addresses and Japanese phone formats.

2. Add fields. Click "Add Field" to add columns to your dataset. Give each field a name and choose a data type from the dropdown. You can also set a null percentage if you want some values to be empty, which is useful for testing how your application handles missing data.

3. Use a preset. If you're in a hurry, click one of the preset buttons (Users, E-commerce, Employees, etc.) to instantly populate a common schema. You can then customize it by adding, removing, or renaming fields.

4. Generate and export. Set the number of rows you need (up to 50,000) and click Generate. Preview the data in table format, then switch to JSON, CSV, SQL, or TSV. Copy to clipboard or download as a file.

Why Use Fake Data for Testing?

Using real user data in development and testing environments creates serious privacy and compliance risks. Fake data generators solve this problem by producing realistic-looking data that has no connection to real people. This is especially important when working with personally identifiable information like names, email addresses, phone numbers, and credit card numbers.

Realistic test data also helps you catch bugs that wouldn't appear with dummy values like "test123" or "John Doe." When your test data includes a variety of name lengths, special characters, different address formats, and edge cases, your application gets tested more thoroughly.

Supported Data Types

This generator supports over 20 data types organized into logical categories. Personal data includes first names, last names, full names, email addresses, phone numbers, and usernames. Address data covers street addresses, cities, states, ZIP codes, and countries. Business data includes company names, job titles, and department names. Technical data covers UUIDs, IP addresses (v4 and v6), URLs, and user agent strings. Financial data includes credit card numbers (with valid Luhn checksums), currency amounts, and IBAN numbers. You can also generate dates, booleans, numbers within custom ranges, and paragraphs of lorem ipsum text.

Locale-Aware Generation

One of the most common problems with fake data generators is inconsistent locale data. You get a Japanese name paired with a German address and an American phone number. This tool solves that problem by keeping all locale-sensitive fields consistent. When you select Korean as your locale, you'll get Korean names, Korean cities, Korean phone formats, and Korean postal codes.

Currently supported locales include English (US), English (UK), Korean, Japanese, and German. Each locale includes curated datasets for names, cities, street patterns, and phone number formats.

Save and Reuse Schemas

If you generate the same kind of data frequently, you can save your schema configuration to your browser's local storage. The next time you visit, load it back with one click. You can also export your schema as a JSON file to share with teammates or use across different devices. Import a schema file, and all your fields, types, and null percentages are restored instantly.

Frequently Asked Questions

Is the generated data truly random?

Yes. Each generation produces a fresh set of random data. Names, addresses, and other values are picked randomly from curated datasets, and numeric values use JavaScript's built-in random number generator. Credit card numbers are generated with valid Luhn checksums but are not real card numbers.

Is there a row limit?

There is no hard limit. You can generate up to 50,000 rows in a single batch. Because everything runs in your browser, very large datasets (over 10,000 rows) may take a moment to generate and render, depending on your device's performance.

Is my data sent to any server?

No. All data generation happens entirely in your browser using JavaScript. No data, schemas, or configurations are transmitted to any server. This tool works even when you're offline (after the initial page load).

Can I use this data in production?

This tool is designed for development, testing, and demonstration purposes. The generated data should not be used to impersonate real people or organizations. Credit card numbers pass Luhn validation but are not connected to real accounts.