Mock Data Generator
Generate realistic fake data for testing, development, and prototyping. Define your schema, choose a format, and export instantly.
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Preset Templates
Schema Builder
Generation Settings
1 to 1,000 records
Same seed = same output
Output
[
{
"id": "97da2849-d73e-4b43-aa90-7d090402c802",
"name": "Rebecca Clark",
"email": "stephaniemoore@protonmail.com"
},
{
"id": "893a34bd-8344-41aa-ae1f-6f210579e1be",
"name": "Sarah Hill",
"email": "barbaralewis56@zoho.com"
},
{
"id": "e69595b4-7dbf-4e68-91b5-ce17d2f2bb36",
"name": "William Torres",
"email": "lisa.lopez@mail.com"
},
{
"id": "c62d50ba-ee39-4720-ab44-503f9f228466",
"name": "Anthony Nguyen",
"email": "bettyjackson@zoho.com"
},
{
"id": "9893545a-32b5-4150-a376-bec72d8de729",
"name": "Stephanie Lopez",
"email": "matthewwalker84@aol.com"
},
{
"id": "b0128acf-dadd-4957-ba5f-a5d2501abfe7",
"name": "Dorothy Davis",
"email": "sarahdavis@gmail.com"
},
{
"id": "9bcc3a87-7765-4428-988a-6202f1d681d0",
"name": "Nancy Gonzalez",
"email": "brian.young66@gmail.com"
},
{
"id": "c8c82110-4aa8-4f06-94d8-3ff48dea9c47",
"name": "Timothy Walker",
"email": "amanda.walker76@icloud.com"
},
{
"id": "4aad6e5e-658d-49db-84f7-4acbb2de8717",
"name": "Laura Nguyen",
"email": "anthony.harris@mail.com"
},
{
"id": "02116dda-104b-44da-be51-a3744b8791cb",
"name": "Ryan Miller",
"email": "patriciajohnson@hotmail.com"
}
]Advertisement
How to Use the Mock Data Generator
The Mock Data Generator helps developers create realistic fake data for testing, prototyping, and development without relying on external APIs or libraries. Every piece of data is generated entirely in your browser, ensuring speed and privacy. Whether you need a handful of user records for a UI mockup or a thousand rows of transaction data for load testing, this tool has you covered.
Start by choosing a preset template such as Users, Products, Blog Posts, or Transactions. Each preset loads a curated set of fields with appropriate data types. You can also build your own schema from scratch using the schema builder. Add fields, name them to match your database columns or API shape, and select from over 25 data types including UUID, full name, email, phone number, street address, company, boolean, integer, paragraph, hex color, IPv4 address, and more.
Once your schema is defined, set the number of records you want (anywhere from 1 to 1,000) and pick your output format. JSON is ideal for pasting into API mocking tools, seeding databases, or feeding into front-end components. CSV is perfect for spreadsheet imports, data analysis, and legacy systems that consume tabular data. TypeScript mode generates both a typed interface definition and the data array, giving you type-safe mock data ready to drop into any TypeScript project.
For reproducible output, enter a seed string. The tool uses a deterministic pseudo-random number generator (mulberry32) so that the same seed always produces the same data. This is invaluable for snapshot testing, writing fixtures, or sharing a specific dataset with your team via the share link.
The generated output can be copied to your clipboard with one click or downloaded as a .json, .csv, or .ts file. The stats bar shows the record count, field count, and total output size so you know exactly what you're working with. Reorder fields with the up and down arrows, remove any field with the delete button, and add new fields at any time. The output updates automatically whenever your schema, count, or format changes.
Frequently Asked Questions
What is mock data and why do developers need it?
Mock data is realistic but fake information used during software development and testing. Developers need it to populate databases, test UI layouts, validate API responses, and demonstrate features without using real user data. It speeds up development and protects privacy.
What output formats does the Mock Data Generator support?
The generator supports three output formats: JSON (ideal for APIs and JavaScript applications), CSV (great for spreadsheets and data imports), and TypeScript (generates a typed interface along with the data array, perfect for type-safe projects).
Is the generated data realistic enough for testing?
Yes. The tool generates contextually appropriate data for each field type. Names come from common real-world name pools, emails are properly formatted with realistic domains, phone numbers follow US formatting conventions, addresses use real city and state combinations, and UUIDs follow the v4 specification.
What does the seed option do?
The seed option makes data generation deterministic. When you provide the same seed string, the generator produces the exact same output every time. This is useful for creating reproducible test fixtures, sharing specific datasets with teammates, and writing consistent automated tests.
Is my data processed on a server?
No. All data generation happens entirely in your browser using a client-side pseudo-random number generator. Nothing is sent to any server. This makes the tool fast, private, and usable offline once the page has loaded.
How many records can I generate at once?
You can generate between 1 and 1,000 records per batch. For most development and testing purposes, 10 to 100 records is sufficient. The output is generated instantly regardless of count, and you can copy or download the result with a single click.