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

Ultra-Fast In-Memory Persistence with Eclipse Store

NoSQL and SQL databases can be impressive and powerful when handling their target use cases. However, users seeking optimal performance need to be aware of other aspects that can influence the application in terms of processing efficiency, speed, and even code design. In this regard, one example can be mentioned upfront: most of these database solutions will require some sort of mapping between the database schema and the application data models. As you can imagine, the mapping needs to happen every single time data flows back and forth between the application and the database. This characteristic, known as object-relational impedance mismatch, has a high potential to impact most of the database types we’ve mentioned so far – SQL and NoSQL.

In this chapter, we will discuss another database paradigm, in-memory databases. Adding to the significant performance boost, this is definitely the type of database to be leveraged...