Mock Data Generator
Define your fields, pick a row count, and export realistic test data as JSON, CSV, or SQL.
[
{
"id": "0604a120-c79e-4a1c-aa15-d9668fc6517f",
"first_name": "Anita",
"last_name": "Berners-Lee",
"email": "[email protected]",
"status": "active"
},
{
"id": "243176c2-ab2e-4aa9-8cc0-9e1e7b91561d",
"first_name": "Carol",
"last_name": "Cerf",
"email": "[email protected]",
"status": "active"
},
{
"id": "2823188f-8d41-42d5-b936-f81e529723cb",
"first_name": "Vint",
"last_name": "Gosling",
"email": "[email protected]",
"status": "pending"
},
{
"id": "9ac72ad0-d1ed-4e33-98bd-f3b49aa544db",
"first_name": "Barbara",
"last_name": "Stroustrup",
"email": "[email protected]",
"status": "active"
},
{
"id": "f714827a-693d-4f4e-8184-78e706dcb8fb",
"first_name": "Hedy",
"last_name": "Allen",
"email": "[email protected]",
"status": "suspended"
},
{
"id": "7679be65-b6a2-42e9-a5b0-6bbb5749d5f0",
"first_name": "Alan",
"last_name": "Johnson",
"email": "[email protected]",
"status": "suspended"
},
{
"id": "e28f54fa-1cf4-49a2-9214-870e01978302",
"first_name": "Shafi",
"last_name": "Shaw",
"email": "[email protected]",
"status": "pending"
},
{
"id": "fbae0bd3-3f45-4248-93bc-b06cd5717c3c",
"first_name": "Barbara",
"last_name": "Perlman",
"email": "[email protected]",
"status": "suspended"
},
{
"id": "db57760f-4fae-42b2-b35d-7786ccf0661e",
"first_name": "Bjarne",
"last_name": "Turing",
"email": "[email protected]",
"status": "suspended"
},
{
"id": "f7f73b9e-3cb1-436c-abb4-759b839c2509",
"first_name": "Barbara",
"last_name": "Hamilton",
"email": "[email protected]",
"status": "pending"
}
]How to Use
- 1. Define your fields — give each a name and pick a data type.
- 2. Set how many rows you need.
- 3. Choose JSON, CSV, or SQL output.
- 4. Copy or download the result.
Why Use Fake Data
Building against an empty database hides problems. Long names break layouts, missing values expose null handling, and a table with three rows never reveals a pagination bug. Realistic volume surfaces those issues while they are still cheap to fix.
Using generated data also keeps real customer records out of development and staging environments, which is both a privacy obligation and a practical safeguard — nobody wants a test email blast reaching real addresses.
That is why the generated values use reserved ranges: emails end in example.com, a domain RFC 2606 permanently reserves for documentation, and phone numbers use the fictional 555-01xx block. Even if a test system accidentally tries to contact them, nothing reaches a real person.
Related: JSON Formatter, JSON Schema Generator, and JSON to CSV.
Frequently Asked Questions
What is mock data for?
Seeding a development database, building a UI before the API exists, load-testing a form, or producing a realistic demo without exposing real customer records.
Can I export SQL directly?
Yes. Choose the SQL format and set a table name to get ready-to-run INSERT statements, with strings quoted and single quotes escaped.
Is the data deterministic?
No — each generation is random, and the Regenerate button produces a fresh set. If you need a stable fixture, generate once and save the output rather than regenerating each run.
Are the emails and phone numbers real?
No. Emails use the reserved example.com domain, which can never route real mail, and phone numbers follow the reserved 555 test range. Nothing generated here belongs to a real person.
How many rows can I generate?
Up to 500 at a time. That keeps everything instant in the browser; for larger fixtures, generate a few batches or use the output as a template for a script.
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