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Jinx

Introduction

Jinx analyzes your JPA annotations at compile time, generates schema snapshots (JSON), and produces DDL SQL by diffing snapshots over time.

Maven Central Gradle Plugin Portal License

MySQL First · JDK 21+ Required · Latest Version: 0.1.2 · JPA 3.2.0 Supported

Liquibase YAML is supported as an output dialect, but SQL is the primary and most thoroughly validated output format.

Why Jinx?

Jinx exists to make database schema evolution explicit, reviewable, and automation-friendly.

Prevent human error in DDL

DDL is generated from JPA metadata instead of being handwritten. Typos, missing columns, and inconsistent constraints are eliminated before they reach production.

Developer-reviewable migrations

Jinx outputs plain SQL files. Schema changes can be reviewed, discussed, and approved just like application code.

CI/CD-friendly by default

Because Jinx produces SQL files, migrations integrate naturally into existing CI/CD pipelines without requiring a live database connection.

No database required

Schema analysis and diffing operate purely on snapshot files. You can generate and validate migrations without connecting to an actual database.

Migration history without extra runtime tooling

Generated SQL files can be committed to Git. If you do not want to introduce a dedicated migration runtime, Git itself becomes your schema history and audit trail.

Design Philosophy

Compile-time analysis (no reflection)

Jinx performs schema analysis using annotation processing at compile time. It does not rely on runtime reflection and does not strictly follow the reflection-based JPA specification model.

This design is intentional:

  • Deterministic schema generation
  • Zero runtime metadata requirements
  • Compatibility with AOT-oriented build pipelines

As the Java ecosystem continues to reduce reflection usage, Jinx remains naturally aligned with static and reproducible builds.

Output Formats

SQL (Primary)

DDL SQL is Jinx’s first-class output and receives the most validation.

Liquibase YAML (Secondary)

Liquibase output is provided as a compatible dialect for teams that already rely on Liquibase for execution and tracking. It is not the core model, but a translation layer on top of SQL generation.