Mock / Fake Data Generator
Generate realistic fake data from a custom schema as JSON, CSV or SQL — 100% in your browser.
About Mock / Fake Data Generator
Build a schema by adding fields and choosing a type for each — UUID, first/last/full name, email, username, phone, city, country, company, job title, street, zip, date, boolean, number, sentence, color, URL or IPv4. Set how many rows you need and export the result as JSON, CSV or SQL INSERT statements.
Great for seeding databases, testing UIs and writing examples. Everything is generated locally in your browser; no data is uploaded.
How to use Mock Data Generator
- Choose the available fields, row count and JSON, CSV or SQL output format.
- Generate a small sample first and check names, columns and value types before producing a larger fixture.
Limitations and common mistakes
Fake data is useful for development but is not a statistically representative or legally anonymized dataset. Avoid treating generated examples as real user records.
Review SQL quoting and schema compatibility before execution. Do not run generated inserts against a production database without appropriate review and backups.
The tool processes its input locally on your device. Read our privacy policy for analytics, storage and network details.
A users dataset
id: uuid · name: fullName · email: email · age: number
[{ "id": "…", "name": "Ada Khan", "email": "[email protected]", "age": 36 }, …]Switch the output to CSV or SQL, and set the row count up to 1,000.
Frequently asked questions
Which output formats are supported?
JSON (array of objects), CSV (with a header row) and SQL INSERT statements with a configurable table name.
How many rows can I generate?
Up to 1,000 per batch. Click Regenerate for a fresh set.
Can I customize the fields?
Yes. Add or remove fields, rename them and pick from 20 data types including UUID, names, emails, dates, numbers and more.
Is the data uploaded anywhere?
No. All data is generated locally in your browser.
For related tasks, explore UUID Generator and JSON Formatter. Their guides explain the different inputs, assumptions and output formats.