Book Image

Persistence Best Practices for Java Applications

By : Otavio Santana, Karina Varela
Book Image

Persistence Best Practices for Java Applications

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)
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

In conclusion, architecting distributed systems presents unique challenges that must be carefully addressed to ensure the success and effectiveness of the system. Throughout this chapter, we explored some challenges, such as dual-write and microservices with shared databases, and discussed why they could be problematic.

Although initially appealing for data consistency, dual-write can introduce complexity, performance overhead, and data integrity challenges. Similarly, sharing databases between microservices can lead to data coupling, performance bottlenecks, and compromised autonomy. These pitfalls emphasize the importance of carefully considering alternatives, such as event-driven architectures and single databases per microservice, to promote scalability, independence, and maintainability.

We also highlighted the significance of eventual consistency as a model for distributed systems. While it allows temporary data inconsistencies, eventual consistency balances availability...