Converting database schema definitions into visual diagrams helps engineers verify entity relationships, identify circular dependencies, and document relational database architecture. This tool parses SQL DDL directly in your browser to render structured entity relationship diagram (ERD) cards complete with column classifications and table links.

### How the Parser Evaluates DDL The parser scans SQL `CREATE TABLE` commands to identify table boundaries, column definitions, data types, and constraint directives: - **Table Extraction**: Matches table names declared with standard `CREATE TABLE table_name (` syntax, supporting optional schema prefixes or quote wrapping. - **Column & Attribute Mapping**: Identifies column names and SQL data types (such as `INT`, `VARCHAR(255)`, `UUID`, `TIMESTAMP`, or `BOOLEAN`). - **Key Constraints**: Detects `PRIMARY KEY` markers on column lines or table constraints, tagging them with primary key badges. - **Foreign Key Relationships**: Parses `FOREIGN KEY (col) REFERENCES other_table(other_col)` clauses to establish parent-child entity link connections across diagram cards.

### Worked SQL Parsing Example Paste a multi-table SQL definition: ```sql CREATE TABLE users ( id INT PRIMARY KEY, username VARCHAR(50) NOT NULL, email VARCHAR(100) UNIQUE );

CREATE TABLE orders ( order_id INT PRIMARY KEY, user_id INT REFERENCES users(id), total_amount DECIMAL(10, 2) ); ``` The parser generates two relational entity cards: 1. **users**: Displays `id` with a primary key indicator alongside text columns `username` and `email`. 2. **orders**: Displays `order_id` (PK) and identifies `user_id` as a foreign key linking directly to the `users` table.

### Private In-Browser Generation All SQL parsing, regex tokenization, and schema card rendering execute entirely inside your local browser memory using client-side JavaScript. No database structures, column names, or proprietary SQL scripts are transmitted across external networks.