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Why Use wborm?

Native Integration with JDBC

wborm is tailor-made to integrate seamlessly with the wbjdbc library, offering a Python → JDBC → database pipeline that works without heavy dependencies, and with no need for intermediaries like SQLAlchemy or SQLAlchemy-based ORMs.

Compatible with “Forgotten” Databases like Informix

Popular ORM frameworks such as Django ORM, SQLAlchemy, or Tortoise ORM: - Do not support Informix natively - Depend on ODBC connectors or specialized drivers - Focus mainly on mainstream databases like Postgres or MySQL

wborm works effortlessly with: - Informix
- DB2
- Oracle
- Firebird
- Any database compatible with JDBC

Zero Magic, Full Control

Unlike heavy ORMs that hide SQL details: - You get full access to the generated query (.raw_sql()) - You can inspect, customize, and audit the SQL before execution - confirm=True ensures destructive or write actions are explicit

Low Learning Curve

wborm’s API is close to the pandas mindset:

Cliente.select("nome").filter(idade=30).all()

And if needed, you can still do:

pd.DataFrame([c.to_dict() for c in Cliente.all()])

Security First

  • Requires confirm=True for add(), update(), and delete()
  • Blocks updates or deletions without a WHERE clause
  • Wraps operations in transactions (BEGIN WORK / COMMIT / ROLLBACK) automatically

Real Introspection Support

You can do:

generate_model("clientes", conn)

And dynamically get a model with: - Fields - Types - PKs and nullable flags

Combined with wbjdbc, Becomes a Full JDBC Framework for Python

  • wbjdbc manages the JDBC connection
  • wborm maps tables and simplifies querying
  • Together, they form a lightweight, Pythonic alternative to Spring Data — with no Java needed

Perfect for ETL, Inspection, Automation, and Dashboards

Need to expose your Informix ERP data in Power BI or Grafana?
wborm + wbjdbc give you: - Simple transformation/read models - Instant integration with Pandas or Spark - All in pure Python

When to Use wborm

  • You are working with legacy databases via JDBC
  • You need to query Informix, Oracle, Firebird, etc.
  • You want a lightweight and explicit ORM
  • You want to transform data into DataFrames safely and clearly
  • You need automated schema introspection

WBORM: productivity, control, and compatibility where other ORMs won’t go.