In this article, I would like to talk about the Spring Data JPA (Java Persistence API). This library is one of the main building blocks of the Spring framework. It is also a powerful tool that you should know about if you would like to work with persistent data.

I often see that developers who actually use it do not see the whole picture. They miss using some of the most useful abilities of it. Hence, I would like to show you the bigger picture as well as the most meaningful tools to handle your persistent data across your application.

If you are not familiar with Java Spring yet, I recommend you to check out my previous article about it here.

How Long Can a Simple CRUD Repository Be?

Before we jump in, I would like to share a quick introspection on what this framework is capable of doing. Let's see the following code snippet below.

The picture shows the amount of code needed to handle inserting, updating, deleting, and reading data from a single database table using a standard JPA entity model.

These are also known as standard CRUD operations. CRUD is an acronym for Create, Read, Update, and Delete. We also implemented some custom queries in this class that perform various data filtering with this JPA entity. All in all, this is a pretty standard code to build up a persistence tier with JPA in Java.

How Long Is It With Spring Data JPA?

By including and implementing Spring Data JPA into your project, you can remove all of the code and replace it with the following:

We went down from almost 50 lines of code to 5 lines of code without losing any of the functionality. This should give you an idea of how powerful this framework is.

What Is Spring Data JPA?

After we got a taste of what we can achieve with this library, let's talk about how it works is and how it connects to the Java Spring ecosystem.

As I mentioned before, it is considered one of the core projects in Spring's suite of tools.

Spring Data JPA also builds upon and enhances JPA, which stands for Java Persistence API.

Spring Data JPA Features

Most applications have some kind of data store. As your application complexity and feature set grows, you will find that your Data Access Layer and persistence tier code will also grow.

One of the core objectives of Spring Data JPA is to reduce your code and simplify your Data Access Layer, while still maintaining a rich and full-featured set of functionality.

To make this possible, Spring DATA JPA allows you to build intelligent Spring Repository stereotyped interfaces. These repositories are Java interfaces that allow you to define a data access contract.

The Spring Data JPA framework then inspects that contract and automatically builds the interface implementation under the covers for you.

To generate an implementation of your Repository interface, it needs a Query DSL. DSL is an acronym for Domain Specific Language.

The Query Domain Specific Language allows you to create Java interface methods that utilize certain keywords along with JPA entity attributes to perform the work needed.

Spring Data JPA also provides some nice extras, such as auditing, paging, and handling of native SQL queries.

If you need to do something that the Spring Data provider cannot do, it can easily get out of the way and let you code your own implementations.

Summary

In this article, we went through the capabilities of the Spring Data JPA. You got some introspection how it relates to the Spring Framework and the Java Persistence API. I also showed you a quick example of how drastically it can decrease the line of codes of a standard JPA class by serving the same functionality.

For more deeper knowledge I recommend you to read the official Spring documentation here.

In my upcoming articles, I will dive deeper into its' functionalities with provided examples. Stay tuned!