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SQL INSERT Statement Generator

Used by developers, writers, and creators worldwide.

A SQL INSERT statement generator gives you ready-to-run seed data in seconds, without writing a single row by hand. Choose from five table schemas — users, products, orders, employees, or events — set how many rows you need, and get a batched INSERT you can paste straight into MySQL, PostgreSQL, SQLite, or MariaDB. Need 200 order rows to stress-test a GROUP BY query? Done in one click. Seed data quality matters. Placeholder values like 'test1@test.com' or uniform prices can hide bugs that only surface with realistic variance. This tool generates names from multiple cultures, prices with cents, timestamps spread across plausible ranges, and statuses drawn from real enumerations — so your test environment actually behaves like production.

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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 type that matches the schema you want to populate — users, products, orders, employees, or events.
  2. Set the row count to the number of INSERT rows you need for your test or seed scenario.
  3. Click Generate to produce a batched SQL INSERT statement with realistic dummy values.
  4. Review the output to confirm column names align with your schema, then rename any columns via find-and-replace if needed.
  5. Copy the statement and paste it directly into your SQL client, migration file, or seed script, then execute.

Use Cases

  • •Seeding a local users table with 50 rows before writing Cypress login flow tests
  • •Populating a products table to demo a Next.js e-commerce prototype to a client
  • •Generating order records to validate GROUP BY and aggregate queries in PostgreSQL
  • •Creating realistic employee rows for a Metabase or Tableau HR dashboard demo
  • •Pasting generated events data directly into a Flyway or Liquibase migration script

Tips

  • →Generate users first, note the ID range, then generate orders — this way foreign key references stay plausible.
  • →For join query practice, generate 20 users and 50 orders so you get realistic one-to-many result sets.
  • →Wrap the pasted output in BEGIN; ... COMMIT; when inserting into PostgreSQL to make the seed operation atomic and easily reversible.
  • →If your ORM uses snake_case column names, a single find-and-replace pass on the output adapts it in under a minute.
  • →Generate a small batch of 3-5 rows first to verify the schema fits your table before generating the full seed count.
  • →Combine outputs from multiple table types into one .sql file and run them in dependency order: users before orders, products before order_items.

FAQ

are these INSERT statements compatible with PostgreSQL and MySQL

Yes. The output uses standard ANSI SQL with single-quoted strings and ISO 8601 dates, which run without modification in MySQL, PostgreSQL, SQLite, and MariaDB. SQL Server users may need a small tweak to identity column handling, but the rest of the statement is valid as-is.

how do I adapt the output if my column names are different

The generator uses fixed schemas per table type, so column names are predefined. A quick find-and-replace in VS Code or your SQL client is all you need — swap the generated column names for yours and the realistic data values carry over unchanged.

does the orders table handle foreign keys correctly

Order rows reference user_id values within a plausible range, but they are not guaranteed to match rows in a separate users table. If your schema enforces foreign key constraints, generate the users table first or temporarily disable constraint checks before inserting order data.