🤖 AI Database Schema Designer
Describe your app in plain English. AI generates a normalized Entity-Relationship Diagram (ERD) with tables, relationships, and indexes. Export as ready-to-run SQL CREATE statements.
📝 Describe Your App
📊 Generated Schema
📋 How to Use AI Database Schema Designer
Describe Your App
Write a plain English description of your application. Include entities like "users", "products", "orders" and their relationships. Be as specific as you like.
Select Database Type
Choose your preferred database (MySQL, PostgreSQL, etc.). This tailors the SQL syntax, data types, and indexing conventions.
Generate & Review
Click "Generate Schema". The AI will analyze your description and create a normalized ERD, showing tables, columns, keys, and relationships.
Export SQL
Review the generated CREATE statements. Once satisfied, export them to use in your database administration tool or migration script.
❓ Frequently Asked Questions
Normalization is the process of organizing data to reduce redundancy. A normalized ERD typically follows rules like 3NF (Third Normal Form), where data is split into separate tables linked by relationships. For example, user information is stored once and linked to their posts via a user_id foreign key, instead of duplicating user names in every post record.
The AI uses a language model trained to identify entities (nouns like 'user', 'product'), attributes (descriptors like 'email', 'price'), and relationships (verbs like 'has', 'belongs to', 'purchases'). It maps these to database concepts like tables, columns, primary keys, and foreign keys. For best results, use clear, descriptive sentences.
Currently, we support MySQL, PostgreSQL, SQLite, and SQL Server. The main differences are in data types (e.g., MySQL's AUTO_INCREMENT vs PostgreSQL's SERIAL) and index syntax. The generated SQL will match your selection.
Yes. If your description implies a many-to-many relationship (e.g., "posts can have many tags, and tags can belong to many posts"), the designer will automatically create a junction table (like 'post_tags') to resolve it, with appropriate foreign keys and composite indexes.
The current version generates a schema based on your description. For custom edits, you can export the SQL and modify it in your own SQL editor. Future versions may include an interactive editor to tweak tables and relationships directly in the tool.
The export includes CREATE TABLE statements with appropriate columns, data types, primary keys, foreign key constraints, and suggested indexes (e.g., on foreign key columns and frequently queried fields). It aims to be a production-ready starting point.