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Kaumei JDBC Kaumei JDBC

Introduction

Kaumei JDBC is a Java library and annotation processor designed to simplify common SQL operations. It keeps JDBC access straightforward while keeping type safety and predictable performance.

Story & Positioning

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Kaumei JDBC targets teams that want the control of hand-written SQL with improved safety, ergonomics, and observability compared to heavier frameworks. It keeps SQL front and center while compiling the boring plumbing for you.

Problems we address

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  • Hidden work in ORMs: Large frameworks create unpredictable SQL and runtime reflection traps.
  • Boilerplate in plain JDBC: Manual mapping and error handling slow teams down and duplicate logic.
  • Inconsistent mapping layers: Every project reinvents conversions between domain types and SQL columns.

How Kaumei JDBC stands apart

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  • Compile-time checks: Annotation processing generates DAO implementations and validates bindings up front.
  • No reflection in generated code: Generated code is simple Java, so debuggers and profilers show real call stacks.
  • Explicit SQL, reusable mappers: SQL stays in your codebase, converters are shared via annotations, and nothing is recreated at runtime.
  • Designed to be portable: Works with most JDBC drivers and common DI/containers that can wire interfaces.

Outcomes for adopters

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  • Predictable database access paths that are easy to reason about during reviews and incident response.
  • Faster onboarding—new engineers read SQL instead of deciphering meta frameworks.
  • More predictable performance in dev, test, and prod because the generated code matches what runs in production.

How Kaumei JDBC works

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At build time the annotation processor inspects your DAO interfaces and SQL snippets. It validates parameters and generates strongly typed mapper classes. Those classes use plain JDBC, so at runtime you inject a DataSource and obtain a connection. You call the generated methods directly to execute your SQL. There is no container, session, or runtime registry, just the code your build already produced.

Learn more

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Need a deeper comparison or a checklist to decide if Kaumei JDBC fits your use case? See Why Kaumei JDBC for details on alternatives, fit assessment, and trade-offs.