ReferenceBeginner3-5 min reference
Mockaroo
Mockaroo is a web tool for generating large, realistic, schema-shaped datasets — define columns by type, export thousands of rows as CSV/JSON/SQL. It's the fast path when you need bulk, structured data rather than per-object generation in code (that's Faker's job — see the Faker.js sheet). This is a quick reference, not a tutorial.
When Mockaroo fits
- You need hundreds/thousands of rows to seed a DB or test import/ETL.
- You want a file (CSV/JSON/SQL/Excel) rather than in-code generation.
- You want realistic, correlated fields (country → city, name → email) without writing code.
For per-test object creation inside automated tests, prefer Faker.js / factories.
Core concepts
| Concept | Means |
|---|---|
| Field | A column with a chosen type (Name, Email, Number, Date, Custom List…) |
| Type | 140+ built-in data types |
| Blank % | Inject nulls to test missing-data handling |
| Formula | Derive a field from others |
| Schema | Saved set of fields you can reuse |
| Export | CSV, JSON, SQL (INSERTs), Excel |
| API / Mock API | Generate via REST endpoint for dynamic data |
QA tips
- Set a sensible Blank % on optional fields to test null handling.
- Use Custom List types to constrain values to valid enums.
- Export SQL to seed a database directly, or JSON for API stubs.
- Save schemas so a dataset is reproducible across the team.
Common mistakes
- Generating data that ignores the app's validation rules (formats/enums).
- Forgetting referential integrity across related files (ids don't line up).
- Using bulk static files where per-test isolation (Faker/factories) is needed.
- Treating one generated file as reproducible without saving the schema.
// Related resources