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

Database options come in several flavors, and it is crucial to understand the trade-offs with each type. Each data target has specific behaviors, such as SQL having a standard, maturity, several tools, and know-how in its favor. Still, it is pretty hard to work on horizontal scalability.

NoSQL was designed to improve horizontal scalability; however, this came at the cost of less consistency than relational databases are known for.

Finally, NewSQL tries to merge both worlds and bring the benefits of both, but it lacks in both areas.

In the next chapter, we’ll cover more about the architectures and strategies of technologies and how to handle them.