Show Notes
Thorben Janssen joins Marco to talk about the hidden power (and pain) of Java persistence frameworks. Hibernate, JPA, Spring Data, jOOQ: which one should you really use in 2025? From learning SQL the right way to surviving microservices madness, this episode is packed with hard-won lessons from decades of real-world Java work. 💡 Topics in this episode: Hibernate vs JPA vs Jakarta Data When to use jOOQ or Exposed The biggest persistence misconceptions Common performance traps (and how to avoid them) Monoliths, microservices, and “real” architecture decisions How AI might change the way we write queries
⏱️ Timestamps: (00:00) Introduction: From painful early learning to AI-generated annotations (01:02) Meet Thorben Janssen – consultant and trainer for Java persistence (02:11) Early days of Hibernate and the horror of EJB2 (04:33) Main challenges in database access today (06:18) Too many tools: Hibernate, JPA, Spring Data, jOOQ – how to choose (08:15) Why understanding ORM internals really matters (09:20) How juniors should start learning persistence (10:59) SQL skills – why you still need them even with Hibernate or Spring Data (13:48) SQL essentials for beginners: what to learn first (16:01) Why Hibernate became the dominant persistence tool (18:57) Hibernate vs JPA – is there really a difference? (20:35) Hibernate API vs Jakarta Persistence API – which to use (22:10) Criteria API and DSLs for queries (23:43) Strengths and weaknesses of Spring Data JPA (27:26) Jakarta Data vs Spring Data JPA (30:53) Stateful vs stateless data models (33:21) jOOQ, Exposed, and the SQL-centric approach (37:41) Mixing Hibernate and Exposed in one project (39:33) Where Spring Data JDBC fits in (43:24) Starting a new project in 2025 – what stack to choose (45:24) The role of experience and not chasing every new trend (48:50) Monoliths, microservices, and common pitfalls (52:14) Database design vs service design – where to start (59:02) Common database performance issues (01:03:10) Why developers should collaborate with DBAs (01:06:20) Caching problems: when caches make things worse (01:09:29) Reactive database access – what happened to the hype (01:12:33) The "perfect" persistence framework – does it exist? (01:14:40) AI-assisted development and query generation (01:19:43) The AI hype cycle and developer reality (01:20:17) Other persistence models worth learning (graph, full-text search) (01:21:43) Full-text search and graph databases in practice (01:23:25) Integrating AI into applications (01:24:38) Thorben's unpopular opinions (01:26:04) Giveaway announcement (01:27:06) Rapid-fire round: Paderborn, joins, and lazy loading (01:30:00) Closing remarks
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