ddl-generator

To generate a PostgreSQL schema.sql from a JSON data model, you need a tool that reads an immutable model.json file and outputs executable database artifacts. This process creates complete database implementations including resource, event, and junction tables.

Creating sample data and query examples for a PostgreSQL schema involves generating sample_data.sql and query_examples.sql files alongside the main schema. This validates and demonstrates the database plan directly from the defined data model.

Yes, you can enforce naming conventions and foreign keys with ON DELETE RESTRICT during PostgreSQL DDL generation. By using an artifact-driven approach, the schema output strictly follows predefined rules including index creation and Japanese comments.

Artifact-driven SQL generation fully supports junction tables and event tables. It converts an immutable data model into a complete PostgreSQL setup, producing executable schema files that include all required resources, events, and junctions.

A limitation of generating PostgreSQL artifacts from an immutable model is that the output schema strictly enforces ON DELETE RESTRICT for foreign keys and requires Japanese comments, which may not fit all existing database design workflows or conventions.

Yes, you need an existing model.json file placed in the artifacts/{project-name}/ directory. This immutable data model serves as the required input to generate the executable PostgreSQL schema, sample data, and query examples.