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Persistence Best Practices for Java Applications

Persistence Best Practices for Java Applications

By : Otavio Santana, Karina Varela
4.9 (9)
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Persistence Best Practices for Java Applications

Persistence Best Practices for Java Applications

4.9 (9)
By: Otavio Santana, Karina Varela

Overview of this book

Having a solid software architecture breathes life into tech solutions. In the early stages of an application’s development, critical decisions need to be made, such as whether to go for microservices, a monolithic architecture, the event-driven approach, or containerization. In Java contexts, frameworks and runtimes also need to be defi ned. But one aspect is often overlooked – the persistence layer – which plays a vital role similar to that of data stores in modern cloud-native solutions. To optimize applications and data stores, a holistic understanding of best practices, technologies, and existing approaches is crucial. This book presents well-established patterns and standards that can be used in Java solutions, with valuable insights into the pros and cons of trending technologies and frameworks used in cloud-native microservices, alongside good Java coding practices. As you progress, you’ll confront the challenges of cloud adoption head-on, particularly those tied to the growing need for cost reduction through stack modernization. Within these pages, you’ll discover application modernization strategies and learn how enterprise data integration patterns and event-driven architectures enable smooth modernization processes with low-to-zero impact on the existing legacy stack.
Table of Contents (18 chapters)
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1
Part 1: Persistence in Cloud Computing – Storing and Managing Data in Modern Software Architecture
6
Part 2: Jakarta EE, MicroProfile, Modern Persistence Technologies, and Their Trade-Offs
9
Chapter 7: The Missing Guide for jOOQ Adoption
11
Part 3: Architectural Perspective over Persistence

Summary

At this point, we have examined the influence of cloud technology on software architecture design and the importance of design patterns as building blocks for software architects. We compared monolithic and microservices architectures, shedding light on their advantages and disadvantages.

We also explored cloud deployment strategies such as hybrid and multi-cloud models, and how these strategies, combined with managed services such as DbaaS, can speed up the development and delivery of stateful solutions. On the other hand, we also discovered that how we integrate data in distributed systems can impact data management and usage directly. When integrating distributed stateful service, we now know we must be cautious about using anti-patterns such as shared databases and “dual-writes”.

At the end of the chapter, we unveiled the potential of Change Data Capture for data integration in EDA, which increases architectural complexity (more components and technologies...

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