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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

Avoiding data storage-related anti-patterns and bad practices

Several common anti-patterns and bad practices can hinder performance, scalability, and maintainability in an application’s persistence layer. Understanding the difference between anti-patterns and harmful practices is crucial to accurately identify and mitigate these issues.

Anti-patterns are commonly observed in software development and can result from poor design decisions, a lack of understanding, or adherence to outdated practices. Anti-patterns in the persistence layer can include the following:

  • Object-relational impedance mismatch: This anti-pattern occurs when there is a significant disconnect between the object-oriented (OO) model used in the application’s code and the relational model used in the database. It can lead to excessive mapping and conversion logic, performance degradation, and complexity in maintaining data consistency. To avoid this anti-pattern, consider using object-relational...

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