Dev

Dummy SQL Schema Generator

A dummy SQL schema generator saves you from writing repetitive CREATE TABLE boilerplate every time you start a new project or demo. This tool produces realistic, ready-to-run SQL schemas for five common table types — users, products, orders, blog posts, and transactions — across PostgreSQL, MySQL, and SQLite dialects. Each output includes sensible column types, NOT NULL constraints, default values, and CREATE INDEX statements tuned to the columns you'd actually query. Choose your table type and target database dialect, and the generator handles the differences automatically. PostgreSQL gets SERIAL primary keys, JSONB columns where appropriate, and BOOLEAN fields. MySQL gets AUTO_INCREMENT, TEXT for JSON-like data, and TINYINT(1) booleans. SQLite gets its own type-affinity-friendly column definitions. No manual translation needed. The schemas are production-quality starting points, not toy examples. Column names follow common conventions, foreign key relationships are included where they make sense, and timestamp columns use proper defaults like CURRENT_TIMESTAMP. You can paste the output directly into psql, MySQL Workbench, DBeaver, or any migration file and have a working table in seconds. This is especially useful when building tutorials, setting up test databases for ORM experiments, or onboarding teammates who need a realistic schema to work against. Instead of hunting through old projects for a usable CREATE TABLE, generate exactly what you need in one click.

How to Use

  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

  • •Generating a users table with hashed-password and timestamp columns instantly
  • •Creating a products schema for an e-commerce prototype with price and stock fields
  • •Setting up a transactions table to test payment processing logic locally
  • •Building a blog posts schema for a CMS tutorial without writing boilerplate
  • •Testing Sequelize, Prisma, or TypeORM migrations against a realistic base schema
  • •Teaching SQL constraints and index design using concrete, runnable examples
  • •Quickly scaffolding a demo database for a job interview take-home project
  • •Creating SQLite schemas for mobile app prototypes needing offline data storage

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 this dummy SQL schema in a real production database?

Yes, the schemas are solid starting points with proper constraints, defaults, and indexes. You will likely want to rename some columns, adjust VARCHAR lengths to your data requirements, and add any domain-specific columns. Treat the output as a well-structured first draft rather than a final migration.

What are the differences between the PostgreSQL and MySQL schemas?

PostgreSQL schemas use SERIAL or BIGSERIAL for auto-incrementing primary keys, JSONB for semi-structured data, and BOOLEAN for true/false fields. MySQL schemas use AUTO_INCREMENT, TEXT in place of JSONB, and TINYINT(1) for booleans. Index syntax also differs slightly between the two dialects.

Does the SQLite schema work with SQLite version 3?

Yes. The SQLite output uses type affinities like INTEGER, TEXT, and REAL that SQLite 3 handles correctly. It omits PostgreSQL- and MySQL-specific syntax like SERIAL and AUTO_INCREMENT, using INTEGER PRIMARY KEY instead, which triggers SQLite's built-in rowid aliasing for auto-increment behavior.

Does the generated schema include indexes?

Yes. Each schema includes CREATE INDEX statements for columns that are commonly filtered or joined on — for example, email on a users table, user_id on orders, or status on transactions. You can remove indexes you do not need or add composite indexes for your specific query patterns.

How do I run the generated SQL schema?

Copy the output and paste it into your database client: psql for PostgreSQL, MySQL Workbench or the mysql CLI for MySQL, or DB Browser for SQLite. You can also paste it directly into a migration file in Django, Laravel, or any framework that accepts raw SQL migrations.

Can I generate schemas for tables not in the list?

The generator currently covers users, products, orders, blog posts, and transactions — the five most common starting-point tables. For custom tables, use the closest match and modify column names and types. The structure, constraints, and index patterns will still give you a strong foundation to edit from.

Will the schema work with ORMs like Prisma, Sequelize, or SQLAlchemy?

Yes. The generated SQL creates tables that any ORM can introspect or map to models. For Prisma you can run prisma db pull after applying the schema to auto-generate your schema.prisma. For Sequelize or SQLAlchemy, the column names and types map cleanly to their standard field types.

Does the orders or transactions table include foreign key constraints?

Yes. Where relationships are logical — for example, orders referencing a user — the schema includes FOREIGN KEY constraints with ON DELETE behavior defined. This means you need to create referenced tables first, or run the statements in the correct order, which the output is arranged to respect.