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Dummy Database Seed Generator

Used by developers, writers, and creators worldwide.

A dummy database seed generator saves you from writing SQL INSERT statements by hand every time you spin up a fresh environment. Paste the output straight into psql, MySQL Workbench, or a migration file and your database has realistic users, products, orders, or sessions in seconds. The tool supports MySQL, PostgreSQL, and SQLite, each with correct quoting rules and boolean syntax, so switching engines takes one click. Realistic field values — properly formatted emails, decimal prices, ISO timestamps — mean your application validators, ORM mappers, and date-range queries all behave as they would against real data, surfacing bugs that obviously fake strings never would.

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How to use

  1. Choose your options above
  2. Click Generate
  3. Copy your result

Detailed instructions

  1. Select the table schema you want to populate from the Table dropdown: users, products, orders, or sessions.
  2. Choose your SQL dialect — PostgreSQL, MySQL, or SQLite — to match your target database engine.
  3. Set the row count to however many INSERT records you need for your test or seed scenario.
  4. Click Generate to produce ready-to-run SQL statements with realistic fake field values.
  5. Copy the output and paste it into your database client console, seed file, or migration script.

Use Cases

  • •Seeding a local PostgreSQL database with 50 users before a code review demo
  • •Generating orders rows with varied timestamps to debug a Knex date-range query
  • •Populating a SQLite database for a React Native prototype without a live backend
  • •Creating realistic product records to test Stripe price formatting in a staging environment
  • •Adding sessions rows to load-test a background cleanup job in a Docker dev container

Tips

  • →Generate a users table first, then generate orders using the same row count — user_id references will align numerically for simple join testing.
  • →For PostgreSQL, the output uses SERIAL-compatible id values; if your table uses UUID primary keys, swap the id column type before running the script.
  • →Wrap pasted INSERT statements in BEGIN; ... COMMIT; to speed up bulk inserts and make rollback easy if something goes wrong.
  • →When testing pagination or sorting, generate at least 50 rows so edge cases at page boundaries and sort-order ties actually appear in query results.
  • →If your ORM uses underscored column names (created_at, is_active), the generated schema already matches — no column renaming needed for Rails, Django, or Laravel defaults.
  • →For CI pipelines, generate a fixed seed file once and commit it to your repo rather than regenerating each run, ensuring consistent test data across all environments.

FAQ

how do I generate SQL INSERT statements with fake data for testing

Select a table schema (users, products, orders, or sessions), pick your SQL dialect, and set the row count. The generator outputs ready-to-run INSERT statements you can paste directly into a database client, a .sql seed file, or a Knex/Flyway migration script.

does the generated SQL work with PostgreSQL, MySQL, and SQLite

Yes — each dialect gets its own correct syntax. PostgreSQL uses double-quoted identifiers and TRUE/FALSE booleans, MySQL uses backtick quoting and tinyint booleans, and SQLite uses permissive text-based dates. Switching the dialect dropdown regenerates all statements instantly.

is it safe to run this fake SQL data in a production database

No. The output is entirely fictional and meant only for development, staging, and CI environments. Running it in production risks triggering email notifications on fake addresses, corrupting real records, and creating compliance issues if your schema holds regulated data.