Test Data & Mock Data Generator

Build a table schema by adding typed fields (name, e-mail, phone, numbers, dates, UUIDs, words and more), choose a row count and an optional reproducible seed, then generate realistic random rows as CSV, TSV, JSON, HTML or bulk SQL INSERT statements for MySQL, PostgreSQL, SQLite or SQL Server. Handy for database seeding, UI mockups, load samples and API fixture responses. Every value is synthetic — no real personal data is produced, and everything runs entirely locally.
Rows: 1-5000 Seed (optional):
Output format:
SQL dialect: Table:
Fields (table schema)
Each field has a column name, a data type with its own options, an optional NULL rate (0-100%) and a Unique flag. Typed values regenerate automatically as you edit.
Preview
Output
HTML Preview
About generated data:
Values are drawn from synthetic pools — any resemblance to a real person, company or address is coincidental. US phone numbers use the reserved fictitious 555-01xx exchange range and e-mail always uses reserved example.* domains (RFC 2606), so nothing generated here is dialable or reachable. Leaving the seed empty uses cryptographically-random input; typing the same seed reproduces the exact same rows, which is handy for fixtures and regression tests. Generation is capped at 5,000 rows and runs 100% locally.
What is schema-driven data generation?

Instead of hand-typing rows, you describe the shape of the data — a typed field list — and the generator fills each column from a pool of realistic values: names, e-mails, phones, dates, UUIDs. This is the idea behind Faker-style libraries, and it scales: change the schema once and a thousand consistent rows come out the other end as CSV, JSON or SQL INSERTs ready to seed a dev database.

Synthetic data keeps production data out of lower environments — a bug in a load test can leak nothing, because no generated row corresponds to a real customer.