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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

Polyglot persistence is a good path to advance most enterprise applications. It is possible to explore SQL, NoSQL, or any persistence solution with this approach. However, as with any architectural decision, pay attention to the trade-offs; an abstraction can ensure that the choice of database will not impact the business perspective.

Jakarta Data helps standardize behavior and code patterns. It helps us build a universe of capabilities out of several persistence solutions. It is promising solution to increase the capabilities around data persistence patterns on Java, and it is open for help and feedback; join us to make our lives even easier when working with this tool.

It’s now time to explore, at an architectural level, the integration practices that allow us to explore the best out-of-data integration patterns in modern cloud-oriented solutions.

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