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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

Eventual consistency problems

In distributed systems, eventual consistency is a model where data updates are not instantly synchronized across all nodes. Instead, temporary inconsistencies are allowed, and the updates are gradually propagated until the system converges to a consistent state.

In eventual consistency, different nodes in the system may have different views of the data at any given point in time. This is primarily due to network latency, communication delays, and concurrent updates. However, eventual consistency ensures the system reaches a consistent state where all nodes converge on the same data.

To address the challenges and potential problems associated with eventual consistency, several techniques and mechanisms can be employed:

  • Conflicts can occur when multiple updates are made to the same data simultaneously. To ensure consistency, conflict resolution mechanisms are used to determine how these conflicts should be resolved. Different techniques, including...

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