JPA vs Hibernate in Spring: Understanding the Difference Through Real Examples

If you’re diving into Java enterprise development, you’ve likely encountered the terms JPA and Hibernate. While often mentioned in the same breath, these technologies serve different purposes in your application’s persistence layer. In this article, I’ll break down their relationship, show you how to identify which is being used in your Spring applications, and explain why one approach might be preferred over the other.

The Relationship: Specification vs Implementation

The first time I encountered both terms in a project, I was confused. Were they competing technologies? Could I use both? Here’s the simplest way to understand them:

JPA (Java Persistence API) is a specification - essentially a blueprint that defines how persistence should work in Java applications. It provides interfaces and annotations but doesn’t include actual code to perform database operations.

Hibernate is an implementation of the JPA specification - it provides the actual code that does the heavy lifting of converting Java objects to database records and vice versa.

Think of it like this: JPA is the architectural plan, while Hibernate is the construction company that builds according to that plan.

Identifying What’s Used in Your Spring Application

When I inherited a legacy Spring application, I needed to figure out whether it was using pure Hibernate or JPA with Hibernate. Here are the telltale signs I looked for:

1. Check the Dependencies

In your pom.xml (Maven) or build.gradle (Gradle), look for:

JPA with Hibernate implementation:

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>

Direct Hibernate usage:

<dependency>
    <groupId>org.hibernate</groupId>
    <artifactId>hibernate-core</artifactId>
    <version>5.6.10.Final</version>
</dependency>

2. Examine the Import Statements

One of the quickest ways I’ve found to identify the approach is to look at the imports:

JPA-focused approach:

import javax.persistence.Entity;
import javax.persistence.Id;
import org.springframework.data.jpa.repository.JpaRepository;

Hibernate-specific approach:

import org.hibernate.Session;
import org.hibernate.SessionFactory;
import org.hibernate.annotations.DynamicUpdate;

3. Look at Repository Implementations

The difference becomes obvious when you examine how data access is implemented:

JPA Repository (clean and simple):

public interface UserRepository extends JpaRepository<User, Long> {
    List<User> findByEmailContaining(String email);
}

Hibernate Direct Approach (more verbose):

public class UserRepository {
    private final SessionFactory sessionFactory;
    
    public User findById(Long id) {
        Session session = sessionFactory.getCurrentSession();
        return session.get(User.class, id);
    }
}

Why JPA with Hibernate Often Wins in Spring Applications

After working on multiple projects, I’ve found that using JPA with Hibernate implementation (particularly through Spring Data JPA) offers significant advantages:

Simplified Repository Layer

The first time I refactored a Hibernate-heavy codebase to use Spring Data JPA, I was amazed at how much code I could delete. With interfaces that extend JpaRepository, you get dozens of ready-to-use methods (findById, save, findAll) with zero implementation code.

No Manual Session Management

I still remember the pain of forgetting to close Hibernate sessions and the resulting connection leaks. With Spring Data JPA, the framework handles all session management automatically:

The old way (Hibernate direct):

public User getUserById(Long id) {
    Session session = sessionFactory.openSession();
    try {
        session.beginTransaction();
        User user = session.get(User.class, id);
        session.getTransaction().commit();
        return user;
    } catch (Exception e) {
        session.getTransaction().rollback();
        throw e;
    } finally {
        session.close();
    }
}

The new way (Spring Data JPA):

public User getUserById(Long id) {
    return userRepository.findById(id).orElse(null);
}

The code speaks for itself!

Transaction Management: The Hidden Complexity

One area where I previously struggled was understanding transaction management in Spring JPA applications. Here’s what I’ve learned:

Repository Methods Are Already Transactional

Many developers don’t realize that Spring Data JPA repository methods already have built-in transaction management. Methods like save(), delete(), and even the query methods are annotated with @Transactional internally.

For simple operations, you don’t need additional transaction configuration:

// Already transactional - no additional annotation needed
public User createUser(User user) {
    return userRepository.save(user);
}

When You Need Service-Level Transactions

However, I’ve found that service-level transactions become crucial in these scenarios:

1. When operations span multiple repositories
2. When you need multiple operations to be atomic
3. When you need custom transaction attributes

Here’s a real-world example from a banking application I worked on:

@Service
public class TransferService {
    @Autowired 
    private AccountRepository accountRepo;
    
    @Transactional
    public void transferMoney(long fromId, long toId, BigDecimal amount) {
        Account from = accountRepo.findById(fromId).orElseThrow();
        Account to = accountRepo.findById(toId).orElseThrow();
        
        from.setBalance(from.getBalance().subtract(amount));
        to.setBalance(to.getBalance().add(amount));
        
        accountRepo.save(from);
        accountRepo.save(to);
    }
}

Without the service-level @Transactional, a failure in the second save operation would leave the database in an inconsistent state - money deducted from one account but never added to the other!

Transaction Propagation: The Magic Behind the Scenes

What surprised me when digging deeper was how repository-level transactions interact with service-level transactions. It’s all about propagation:

With the default Propagation.REQUIRED setting:

• If a transaction exists, the method joins it
• If none exists, a new transaction is created

This is why adding @Transactional at the service level ensures that all repository calls within that method become part of a single atomic unit. If any operation fails, everything rolls back cleanly.

Final Thoughts

After working with both approaches across multiple projects, I’ve consistently found that the JPA with Hibernate (Spring Data JPA) approach leads to cleaner, more maintainable code with fewer bugs related to transaction and session management.

That said, there are still cases where direct Hibernate usage makes sense - particularly when you need very specific Hibernate features or maximum performance control. The beauty of Spring is that it allows you to mix both approaches when needed.

The next time you start a new Spring project or join an existing one, knowing these differences will help you navigate the codebase more confidently and make informed architectural decisions.

What’s your experience been with JPA and Hibernate? Have you found particular advantages to one approach over the other? Drop a comment below!