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Dummy SQL Schema Generator

Used by developers, writers, and creators worldwide.

A dummy SQL schema generator eliminates the tedium of writing CREATE TABLE boilerplate from scratch every time you prototype or spin up a test database. Pick one of five table types — users, products, orders, blog posts, or transactions — then choose your target dialect: PostgreSQL, MySQL, or SQLite. The output includes proper column types, NOT NULL constraints, default values, and CREATE INDEX statements tuned to columns you'd actually query. Dialect differences are handled automatically. PostgreSQL gets SERIAL primary keys and BOOLEAN fields. MySQL gets AUTO_INCREMENT and TINYINT(1). SQLite gets INTEGER PRIMARY KEY with correct type affinities. Paste the result straight into psql, MySQL Workbench, or a migration file and have a working table in seconds.

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How to use

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

Detailed instructions

  1. Select your Table Type from the dropdown — choose the table that best matches your use case, such as users, products, or orders.
  2. Select your SQL Dialect — pick PostgreSQL, MySQL, or SQLite to match the database you are working with.
  3. Click Generate to produce a complete CREATE TABLE statement with columns, constraints, and indexes.
  4. Copy the generated SQL using the copy button, then paste it into your database client, CLI, or migration file.
  5. Modify column names, data types, or constraints as needed before committing the schema to your project.

Use Cases

  • •Running prisma db pull against a generated PostgreSQL users schema to auto-scaffold a schema.prisma file
  • •Seeding a local MySQL orders table with foreign key constraints to test payment processing logic in Postman
  • •Applying a SQLite transactions schema in DB Browser for SQLite to prototype an offline-capable mobile app
  • •Pasting a blog_posts CREATE TABLE into a Django or Laravel raw SQL migration to skip writing boilerplate
  • •Testing Sequelize or TypeORM model mappings against a realistic products schema with price and stock columns

Tips

  • →Generate the users table first when building a multi-table app — other tables like orders and transactions reference it via foreign keys.
  • →If you plan to use Prisma, apply the SQL schema first, then run prisma db pull to auto-generate your models without manual schema writing.
  • →For SQLite in a mobile or local-first app, the generated schema works as-is inside a React Native SQLite plugin or Electron app with better-sqlite3.
  • →The generated indexes cover single-column lookups. Add composite indexes manually for queries that filter on two columns simultaneously, like status AND created_at.
  • →When teaching SQL, use the MySQL dialect for beginners — its syntax is more widely documented in tutorials and beginner courses than PostgreSQL.
  • →Copy the schema into a seed script alongside your INSERT statements so teammates can spin up a matching local database in one command.

FAQ

can I use the generated SQL schema as a starting point for a real production database

Yes — the schemas include proper constraints, indexes, and defaults that hold up in production. You'll want to rename columns, adjust VARCHAR lengths to your actual data, and add any domain-specific fields before running a final migration.

what's the difference between the PostgreSQL and MySQL output

PostgreSQL schemas use SERIAL or BIGSERIAL for auto-increment, JSONB for semi-structured columns, and BOOLEAN for true/false fields. MySQL uses AUTO_INCREMENT, TEXT in place of JSONB, and TINYINT(1) for booleans. Index syntax also differs slightly, and the generator handles all of that automatically.

does the SQLite schema support auto-increment the same way PostgreSQL does

SQLite uses INTEGER PRIMARY KEY instead of SERIAL or AUTO_INCREMENT, which triggers its built-in rowid aliasing to deliver the same auto-increment behavior. The output sticks to SQLite type affinities — INTEGER, TEXT, REAL — and drops any PostgreSQL- or MySQL-specific syntax that SQLite 3 would reject.