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Overview
DDL ↔ Entity converts a SQL
How to Use This Tool
Step 1 - choose a direction: DDL -> Entity or Entity -> DDL. Step 2 - pick the target language and SQL dialect. Step 3 - toggle ORM annotations, Lombok, and column comments as needed, and fill in the package or namespace. Step 4 - paste your source into the appropriate panel; the other panel updates automatically. Use the Sample button to load a demo table.
Common Use Cases
Back-end developers turning DBA-provided DDL into JPA / Entity Framework / GORM entity classes; front-end and full-stack teams generating strongly-typed TypeScript models directly from database schemas; data engineers reverse-engineering DDL from struct or dataclass definitions when bootstrapping a new environment; teams standardising the mapping between snake_case columns and camelCase / PascalCase fields.
Technical Details
The DDL parser understands common column definitions -
VARCHAR(n), DECIMAL(p,s), BIGINT, TINYINT(1), DATETIME, JSON and so on - and normalises them to a language-agnostic type set. The reverse pass reads the entity class with a lightweight parser and rebuilds the DDL with dialect-specific tweaks (AUTO_INCREMENT vs SERIAL, TINYINT(1) vs BOOLEAN, BYTEA vs BLOB, etc.). Column names are converted to snake_case and field names to PascalCase / camelCase automatically.Privacy & Security
Parsing and code generation both run entirely in your browser; no DDL or entity code is uploaded to any server, so it is safe to use with schemas that contain business-sensitive table or column names.