Spring Boot and PostgreSQL are a popular combination for building reliable and scalable Java backend applications.

Spring Boot simplifies application development by providing auto-configuration, dependency injection, web support, and integrations with database technologies. PostgreSQL provides a powerful relational database with strong transactions, constraints, indexing, and advanced SQL features.

A typical application architecture looks like this:

Client
  ↓
Spring Boot REST API
  ↓
Service Layer
  ↓
Repository Layer
  ↓
Hibernate / JPA
  ↓
PostgreSQL

In this guide, we’ll learn how to connect PostgreSQL with Spring Boot and build a database-driven application.

We’ll cover:

• Setting up PostgreSQL
• Creating a Spring Boot project
• Adding PostgreSQL dependencies
• Configuring the database
• Creating entities
• Using Spring Data JPA
• CRUD operations
• Repository methods
• REST APIs
• Relationships
• Transactions
• Validation
• Pagination and sorting
• PostgreSQL queries
• Hibernate
• Database migrations
• Performance optimization
• Common errors
• Production best practices

---

Why Use PostgreSQL with Spring Boot?

Spring Boot and PostgreSQL work well together because both provide strong support for enterprise backend development.

Spring Boot provides:

• Dependency injection
• REST API development
• Auto-configuration
• Spring Data
• Transaction management
• Security integration
• Validation
• Production-ready features

PostgreSQL provides:

• ACID transactions
• Strong data integrity
• Powerful SQL
• Foreign keys
• Indexes
• JSONB
• Full-text search
• Advanced data types
• Excellent scalability

Together, they provide a strong foundation for modern backend applications.

---

PostgreSQL + Spring Boot Architecture

A typical Spring Boot application can be structured like this:

Frontend
   ↓
REST Controller
   ↓
Service
   ↓
Repository
   ↓
JPA / Hibernate
   ↓
JDBC Driver
   ↓
PostgreSQL

Each layer has a specific responsibility.

Controller

Handles HTTP requests and responses.

Service

Contains business logic.

Repository

Handles database operations.

Hibernate / JPA

Maps Java objects to relational database tables.

PostgreSQL

Stores the actual application data.

---

Prerequisites

Before starting, you should have:

• Java installed
• Spring Boot knowledge
• Basic SQL knowledge
• PostgreSQL installed
• Maven or Gradle

Check Java:

java --version

Check PostgreSQL:

psql --version

---

1. Create a PostgreSQL Database

First, create a database.

Using psql:

CREATE DATABASE spring_boot_app;

You can connect to it:

psql -d spring_boot_app

You can also create and manage PostgreSQL databases using a graphical database client.

---

2. Create a Spring Boot Project

You can create a Spring Boot project using Spring Initializr.

For this application, you’ll typically need:

Spring Web
Spring Data JPA
PostgreSQL Driver
Validation

A Maven project will contain a pom.xml file.

---

3. Add PostgreSQL Dependency

If you’re using Maven, add the PostgreSQL JDBC driver:

<dependency>
    <groupId>org.postgresql</groupId>
    <artifactId>postgresql</artifactId>
    <scope>runtime</scope>
</dependency>

For Spring Data JPA:

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

For REST APIs:

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

Spring Boot manages compatible dependency versions through its dependency management.

---

4. Configure PostgreSQL

The main configuration is usually stored in:

src/main/resources/application.properties

For example:

spring.datasource.url=jdbc:postgresql://localhost:5432/spring_boot_app
spring.datasource.username=postgres
spring.datasource.password=your_password

spring.jpa.hibernate.ddl-auto=update
spring.jpa.show-sql=true
spring.jpa.properties.hibernate.format_sql=true

The important properties are:

spring.datasource.url
spring.datasource.username
spring.datasource.password

These tell Spring Boot how to connect to PostgreSQL.

---

5. Use Environment Variables for Credentials

Don’t commit database passwords into your source code.

Instead of:

spring.datasource.password=my-secret-password

use an environment variable:

spring.datasource.password=${DB_PASSWORD}

You can similarly configure:

spring.datasource.username=${DB_USERNAME}
spring.datasource.url=${DATABASE_URL}

This is much safer for production deployments.

---

6. Understanding the JDBC URL

A PostgreSQL JDBC URL looks like:

jdbc:postgresql://localhost:5432/spring_boot_app

The structure is:

jdbc:postgresql://
    host
    :
    port
    /
    database

For example:

localhost

is the database server.

5432

is PostgreSQL’s commonly used default port.

spring_boot_app

is the database name.

---

7. Create an Entity

Let’s create a simple User entity.

package com.example.demo.user;

import jakarta.persistence.*;

@Entity
@Table(name = "users")
public class User {

    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;

    private String name;

    @Column(unique = true, nullable = false)
    private String email;

    // Getters and setters
}

The @Entity annotation tells JPA that this class represents persistent data.

---

8. Understanding JPA Annotations

Some important annotations are:

@Entity

Marks a Java class as a JPA entity.

@Table

Specifies the database table name.

@Table(name = "users")

@Id

Defines the primary key.

@GeneratedValue

Configures ID generation.

@Column

Customizes column behavior.

For example:

@Column(nullable = false, unique = true)
private String email;

---

9. How Hibernate Maps Java to PostgreSQL

Your Java class:

@Entity
public class User {
    private Long id;
    private String name;
    private String email;
}

can be mapped to a PostgreSQL table:

users
----------------
id
name
email

The relationship is:

Java Object
    ↓
Hibernate
    ↓
SQL
    ↓
PostgreSQL Table

Hibernate acts as the JPA implementation that performs this object-relational mapping.

---

10. Create a Repository

Spring Data JPA makes database access much easier.

Create:

package com.example.demo.user;

import org.springframework.data.jpa.repository.JpaRepository;

public interface UserRepository
        extends JpaRepository<User, Long> {
}

That’s enough to get many common CRUD operations.

You don’t need to manually write SQL for basic operations.

---

11. Built-in Repository Methods

JpaRepository provides methods such as:

findAll()
findById()
save()
deleteById()
existsById()
count()

For example:

List<User> users = userRepository.findAll();

Find a user:

Optional<User> user =
        userRepository.findById(1L);

Save:

userRepository.save(user);

Delete:

userRepository.deleteById(1L);

---

12. Create a Service Layer

It’s usually better to keep business logic outside the controller.

@Service
public class UserService {

    private final UserRepository userRepository;

    public UserService(UserRepository userRepository) {
        this.userRepository = userRepository;
    }

    public List<User> getUsers() {
        return userRepository.findAll();
    }

    public User createUser(User user) {
        return userRepository.save(user);
    }
}

The architecture becomes:

Controller
    ↓
Service
    ↓
Repository
    ↓
PostgreSQL

---

13. Create a REST Controller

Now expose the users through an API.

@RestController
@RequestMapping("/api/users")
public class UserController {

    private final UserService userService;

    public UserController(UserService userService) {
        this.userService = userService;
    }

    @GetMapping
    public List<User> getUsers() {
        return userService.getUsers();
    }

    @PostMapping
    public User createUser(@RequestBody User user) {
        return userService.createUser(user);
    }
}

Now you can use:

GET /api/users

to retrieve users.

And:

POST /api/users

to create a user.

---

14. CRUD Operations

CRUD means:

Create
Read
Update
Delete

These are the most common database operations in backend applications.

---

Create

userRepository.save(user);

---

Read

userRepository.findAll();

or:

userRepository.findById(id);

---

Update

A common approach is:

User user = userRepository.findById(id)
        .orElseThrow();

user.setName("Oliver");

return userRepository.save(user);

---

Delete

userRepository.deleteById(id);

Spring Data JPA generates the required SQL.

---

15. Query Methods

Spring Data JPA can generate queries from method names.

For example:

Optional<User> findByEmail(String email);

You can then call:

userRepository.findByEmail(
    "oliver@example.com"
);

Another example:

List<User> findByName(String name);

Spring Data derives the appropriate query.

---

16. More Complex Query Methods

You can create methods such as:

List<User> findByNameContaining(String name);

or:

List<User> findByEmailAndName(
    String email,
    String name
);

Spring Data JPA interprets these method names and generates queries.

However, extremely complex method names can become difficult to read.

---

17. Using @Query

For more complex queries, use @Query.

For example:

@Query("""
    SELECT u
    FROM User u
    WHERE u.email = :email
""")
Optional<User> findUserByEmail(
    @Param("email") String email
);

This is JPQL, which works with entity models rather than directly referencing database tables.

---

18. Native SQL Queries

Sometimes you need PostgreSQL-specific SQL.

You can use:

@Query(
    value = """
        SELECT *
        FROM users
        WHERE email = :email
    """,
    nativeQuery = true
)
Optional<User> findByEmailNative(
    @Param("email") String email
);

Native queries can be useful when you need database-specific features or complex SQL.

Don’t use native queries everywhere simply because they are available.

---

19. Hibernate vs PostgreSQL

It’s important to understand the roles of each technology.

Spring Boot
    ↓
Spring Data JPA
    ↓
Hibernate
    ↓
JDBC Driver
    ↓
PostgreSQL

Spring Boot

Application framework.

Spring Data JPA

Provides repository abstractions.

Hibernate

JPA implementation and ORM.

JDBC Driver

Allows Java to communicate with PostgreSQL.

PostgreSQL

Database server.

Each component has a different responsibility.

---

20. PostgreSQL and Hibernate Dialect

Modern Hibernate versions can usually detect the database automatically.

In many Spring Boot applications, you don’t need to manually configure a Hibernate dialect.

If a specific configuration is required, it can be provided through application properties.

Avoid adding unnecessary configuration when Spring Boot can handle it automatically.

---

21. Database Schema Management

A common development configuration is:

spring.jpa.hibernate.ddl-auto=update

This tells Hibernate to update the schema based on entity mappings.

Other values include:

none
validate
update
create
create-drop

For example:

spring.jpa.hibernate.ddl-auto=validate

can be useful when you want Hibernate to verify that the schema matches your entity mappings without changing the database.

For production, schema changes are generally better managed with dedicated migration tools rather than relying on automatic Hibernate schema updates.

---

22. Database Migrations

For production applications, consider tools such as:

• Flyway
• Liquibase

A migration might contain:

CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    email VARCHAR(255) UNIQUE NOT NULL
);

Migration tools allow database changes to be:

Versioned
Repeatable
Reviewable
Deployable

This is much safer for larger applications.

---

23. Relationships Between Entities

Real applications have relationships.

For example:

User
 ↓
Orders

One user can have many orders.

In JPA:

@OneToMany(mappedBy = "user")
private List<Order> orders;

The Order entity might contain:

@ManyToOne(fetch = FetchType.LAZY)
@JoinColumn(name = "user_id")
private User user;

The PostgreSQL relationship looks like:

users
  id
   ↑
   │
orders
  user_id

---

24. One-to-Many Relationship

A common example:

One User
   ↓
Many Orders

Entity:

@OneToMany(mappedBy = "user")
private List<Order> orders;

Order:

@ManyToOne
@JoinColumn(name = "user_id")
private User user;

PostgreSQL stores the foreign key in the orders table.

---

25. Many-to-One Relationship

Many orders can belong to one user:

Order 1 ──┐
Order 2 ──┼──→ User
Order 3 ──┘

This is represented by:

@ManyToOne
@JoinColumn(name = "user_id")
private User user;

---

26. Many-to-Many Relationship

Suppose users can have multiple roles and roles can belong to multiple users.

You can model this using:

@ManyToMany
@JoinTable(
    name = "user_roles",
    joinColumns = @JoinColumn(name = "user_id"),
    inverseJoinColumns = @JoinColumn(name = "role_id")
)
private Set<Role> roles;

The database contains a join table:

users
   ↓
user_roles
   ↓
roles

This is a common relational database pattern.

---

27. Lazy Loading

For relationships, Hibernate supports lazy loading.

For example:

@ManyToOne(fetch = FetchType.LAZY)
private User user;

The related entity isn’t necessarily loaded immediately.

Instead, Hibernate can load it when required.

Lazy loading can reduce unnecessary database work, but it must be used carefully to avoid issues such as excessive queries.

---

28. The N+1 Query Problem

One common Hibernate performance issue is the N+1 query problem.

Imagine:

1 query → Get 100 users

Then:
1 query → Orders for user 1
1 query → Orders for user 2
...
1 query → Orders for user 100

This could result in:

101 database queries

instead of a smaller number of well-designed queries.

Potential solutions include:

• Fetch joins
• Entity graphs
• Batch fetching
• DTO projections
• Carefully designed repository queries

Always inspect actual SQL when investigating this problem.

---

29. Transactions in Spring Boot

Spring provides declarative transaction management.

For example:

@Service
public class OrderService {

    @Transactional
    public void createOrder() {

        // Create order

        // Create order items

        // Update inventory
    }
}

If an appropriate runtime exception causes the transaction to roll back, the changes are reverted according to Spring’s transaction rules.

The basic flow is:

BEGIN
  ↓
Operation 1
  ↓
Operation 2
  ↓
Operation 3
  ↓
COMMIT

If the transaction fails:

ROLLBACK

---

30. Why Transactions Matter

Imagine an e-commerce order:

Create Order
      ↓
Create Order Items
      ↓
Decrease Inventory
      ↓
Save Payment Information

If inventory is updated but creating the order fails, your database could become inconsistent.

A transaction allows related database changes to be treated as one logical unit.

---

31. Validation

Spring Boot provides validation support.

For example:

public class CreateUserRequest {

    @NotBlank
    private String name;

    @Email
    @NotBlank
    private String email;
}

Then:

@PostMapping
public User createUser(
        @Valid @RequestBody CreateUserRequest request) {

    return userService.createUser(request);
}

Validation should happen before invalid data reaches your persistence layer.

---

32. Use DTOs Instead of Exposing Entities

A common beginner approach is:

@PostMapping
public User createUser(
    @RequestBody User user
) {
    return userService.createUser(user);
}

For larger applications, DTOs are usually preferable.

For example:

public record CreateUserRequest(
    String name,
    String email
) {}

and:

public record UserResponse(
    Long id,
    String name,
    String email
) {}

Benefits include:

• Better API control
• Validation
• Separation of API and persistence models
• Reduced accidental data exposure

---

33. Pagination

Spring Data provides pagination support.

Repository:

public interface UserRepository
        extends JpaRepository<User, Long> {
}

Controller:

@GetMapping
public Page<User> getUsers(
        Pageable pageable
) {
    return userRepository.findAll(pageable);
}

A request such as:

GET /api/users?page=0&size=20

can retrieve a page of users.

Pagination is important when dealing with large datasets.

---

34. Sorting

You can also use Spring Data sorting.

For example:

Sort sort = Sort.by(
    Sort.Direction.DESC,
    "createdAt"
);

List<User> users =
    userRepository.findAll(sort);

For dynamic sorting from user input, use an allowlist of permitted properties rather than blindly trusting a client-provided field name.

---

35. PostgreSQL Indexes

Indexes are important for database performance.

For example:

CREATE INDEX idx_users_email
ON users(email);

You can also define indexes through JPA:

@Table(
    name = "users",
    indexes = {
        @Index(
            name = "idx_users_email",
            columnList = "email"
        )
    }
)

Indexes can improve reads but add storage and write-maintenance overhead.

Create them based on actual query patterns.

---

36. Unique Constraints

If emails must be unique:

@Column(
    nullable = false,
    unique = true
)
private String email;

This can result in a unique database constraint/index depending on schema generation.

For production database design, explicit migrations are generally preferable for controlling important constraints.

---

37. PostgreSQL JSONB with Spring Boot

PostgreSQL’s JSONB type can be useful for flexible metadata.

For example:

products
----------------------
id
name
price
metadata JSONB

A product could contain:

{
    "color": "black",
    "features": [
        "wireless",
        "compact"
    ]
}

This allows PostgreSQL to store structured relational data alongside flexible metadata.

Mapping JSONB with Hibernate depends on the Hibernate version and mapping strategy you’re using.

---

38. Native PostgreSQL Features

One advantage of using PostgreSQL with Spring Boot is that you can still access PostgreSQL-specific capabilities when needed.

Examples include:

JSONB
Arrays
Full-text search
Window functions
Common table expressions
Advanced indexing

JPA provides an abstraction, but you don’t have to avoid PostgreSQL-specific SQL when your application benefits from it.

---

39. Query Performance

When an application becomes slow, don’t immediately blame Hibernate.

Performance can be affected by:

Application code
     ↓
Hibernate mapping
     ↓
Generated SQL
     ↓
PostgreSQL query plan
     ↓
Indexes
     ↓
Database resources

Use database and application profiling tools to identify the actual bottleneck.

---

40. Logging SQL

During development, you can enable SQL logging.

For example:

spring.jpa.show-sql=true
spring.jpa.properties.hibernate.format_sql=true

This helps you see SQL generated by Hibernate.

For more detailed SQL and parameter logging, use appropriate logging configuration for your Spring Boot and Hibernate version.

Avoid verbose SQL logging in production unless you have a specific diagnostic reason.

---

41. Use EXPLAIN ANALYZE

When a PostgreSQL query is slow, inspect the execution plan.

For example:

EXPLAIN ANALYZE
SELECT *
FROM users
WHERE email = 'oliver@example.com';

This can show:

• Execution time
• Scan type
• Rows examined
• Index usage
• Query plan

This is especially useful when optimizing queries generated by Hibernate.

---

42. Connection Pooling

Spring Boot applications commonly use HikariCP as the JDBC connection pool.

The general architecture is:

Spring Boot
     ↓
HikariCP
     ↓
JDBC
     ↓
PostgreSQL

Connection pooling avoids creating a brand-new database connection for every request.

Pool settings should be tuned according to:

• Database capacity
• Application instances
• Request volume
• Query duration
• PostgreSQL connection limits

More connections aren’t automatically better.

---

43. Production Database Configuration

A production application should avoid development-only settings.

For example, don’t blindly use:

spring.jpa.hibernate.ddl-auto=create-drop

in production.

Instead:

Development
→ Convenient schema management

Production
→ Versioned migrations
→ Controlled schema changes

Migration tools such as Flyway or Liquibase are often a better fit.

---

44. Handling Database Errors

Your API shouldn’t expose internal database errors directly.

Avoid returning:

SQL exception details
Database connection information
Stack traces
Internal table names

Instead, return a safe response:

{
    "message": "Unable to process the request"
}

Log the detailed error on the server using your application’s logging strategy.

---

45. Database Connection Failure

If PostgreSQL isn’t running or the configuration is incorrect, Spring Boot may fail to start or database operations may fail.

Check:

Database host
Database port
Database name
Username
Password
JDBC URL
PostgreSQL availability
Network access

A typical local PostgreSQL URL is:

jdbc:postgresql://localhost:5432/spring_boot_app

---

46. Common Errors

Connection Refused

Usually indicates that PostgreSQL isn’t reachable.

Check whether the PostgreSQL server is running and whether the host and port are correct.

---

Authentication Failed

Check:

Username
Password
PostgreSQL authentication configuration

---

Database Does Not Exist

Make sure the database specified in the JDBC URL actually exists.

---

Relation Does Not Exist

This can happen when the expected table hasn’t been created or the application is connected to the wrong database/schema.

---

LazyInitializationException

This can occur when lazy-loaded data is accessed outside an appropriate persistence context.

The solution should be based on the application’s transaction and data-fetching design rather than simply changing everything to eager loading.

---

47. Avoid FetchType.EAGER Everywhere

A common mistake is changing all relationships to:

fetch = FetchType.EAGER

just to fix lazy-loading problems.

This can cause:

• More database queries
• Larger result sets
• Unnecessary data loading
• Performance problems

Prefer explicit data-fetching strategies based on what each use case actually needs.

---

48. Use Projections for Large Queries

If you only need a few columns, don’t necessarily load the entire entity.

For example:

public interface UserSummary {
    Long getId();
    String getName();
}

You can design repository queries that return only the required fields.

This can reduce unnecessary data transfer and object creation.

---

49. PostgreSQL with Spring Boot Security

For applications with authentication, PostgreSQL can store:

Users
Roles
Permissions
Refresh Tokens
Audit Records

Spring Security handles authentication and authorization, while PostgreSQL provides persistent storage.

A typical architecture:

Client
  ↓
Spring Security
  ↓
Controller
  ↓
Service
  ↓
Repository
  ↓
PostgreSQL

Sensitive credentials should be securely hashed rather than stored as plaintext.

---

50. Testing with PostgreSQL

Database-backed applications should include integration tests.

For example, you can test:

Repository
Service
Controller
Transactions
Database Constraints

For realistic integration testing, tools such as Testcontainers can run PostgreSQL in a container during tests.

This can provide a closer match to the production database environment than replacing PostgreSQL with a different database.

---

51. Development vs Production

A development environment might use:

Local PostgreSQL
Simple credentials
DDL auto-update
Verbose SQL logging

Production should generally use:

Managed PostgreSQL
Environment-based credentials
Database migrations
Controlled logging
Backups
Monitoring
Connection pool tuning

Keeping these environments separate helps avoid accidental production changes.

---

52. Secure PostgreSQL Credentials

Use environment variables or a secrets-management system.

For example:

spring.datasource.username=${DB_USERNAME}
spring.datasource.password=${DB_PASSWORD}

Don’t commit credentials to Git.

Also make sure database users have only the permissions they actually need.

---

53. Database Backups

A production PostgreSQL database should have a backup and recovery strategy.

Don’t assume:

“The database provider will handle everything.”

You should understand:

Backup
↓
Retention
↓
Recovery
↓
Testing

A backup that has never been tested may not provide the recovery confidence you expect.

---

54. Complete Project Structure

A maintainable Spring Boot application might look like:

src/
└── main/
    ├── java/
    │   └── com/example/app/
    │       ├── controller/
    │       ├── service/
    │       ├── repository/
    │       ├── entity/
    │       ├── dto/
    │       ├── exception/
    │       └── config/
    │
    └── resources/
        ├── application.properties
        └── db/
            └── migration/

A typical request flow is:

Controller
    ↓
DTO
    ↓
Service
    ↓
Repository
    ↓
Hibernate
    ↓
JDBC
    ↓
PostgreSQL

---

55. Example CRUD Flow

Suppose a client sends:

POST /api/users

with:

{
    "name": "Oliver",
    "email": "oliver@example.com"
}

The flow is:

HTTP Request
     ↓
Controller
     ↓
Validation
     ↓
Service
     ↓
Repository
     ↓
Hibernate
     ↓
JDBC Driver
     ↓
PostgreSQL
     ↓
INSERT
     ↓
Response

This is the basic pattern behind many Spring Boot applications.

---

56. Best Practices

Use PostgreSQL for Relational Data

Take advantage of constraints, relationships, transactions, and SQL.

Use Spring Data JPA for Common CRUD

It reduces repetitive persistence code.

Understand SQL

Using JPA doesn’t mean you can ignore SQL.

Understanding SQL helps you write better queries and diagnose performance issues.

Use DTOs

Don’t expose persistence entities blindly through APIs.

Use Transactions

Use @Transactional where multiple operations need consistent behavior.

Use Migrations

Prefer Flyway or Liquibase for controlled schema changes.

Add Appropriate Indexes

Index frequently queried columns based on real workload.

Avoid N+1 Queries

Inspect generated SQL and use suitable fetching strategies.

Use Connection Pooling

Let the application reuse database connections.

Keep Credentials Secure

Use environment variables or a secrets-management solution.

---

PostgreSQL + Spring Boot Cheat Sheet

Component	Purpose
Spring Boot	Application framework
Spring Data JPA	Data-access abstraction
Hibernate	ORM / JPA implementation
JDBC Driver	Java ↔ PostgreSQL communication
PostgreSQL	Relational database
HikariCP	Connection pooling
Flyway / Liquibase	Database migrations
Testcontainers	Database integration testing

---

Final Thoughts

PostgreSQL and Spring Boot make an excellent stack for building modern Java backend applications.

The basic architecture is:

Spring Boot
     ↓
Spring Data JPA
     ↓
Hibernate
     ↓
JDBC
     ↓
PostgreSQL

Spring Boot handles the application and API layer, while PostgreSQL provides reliable data storage, transactions, relationships, constraints, and powerful querying.

To become comfortable with this stack, learn these concepts in order:

1. PostgreSQL Basics
       ↓
2. SQL CRUD
       ↓
3. Spring Boot Basics
       ↓
4. Spring Data JPA
       ↓
5. Entity Mapping
       ↓
6. Repository Queries
       ↓
7. REST APIs
       ↓
8. Relationships
       ↓
9. Transactions
       ↓
10. Pagination
       ↓
11. Indexing
       ↓
12. Query Optimization
       ↓
13. Database Migrations
       ↓
14. Production Practices

The most important thing is not simply learning how to connect Spring Boot to PostgreSQL.

You should understand what happens behind the scenes:

Java Object
    ↓
JPA
    ↓
Hibernate
    ↓
SQL
    ↓
JDBC
    ↓
PostgreSQL

Once you understand this flow, you’ll be able to build, troubleshoot, and optimize database-driven Spring Boot applications much more confidently.

Spring Boot simplifies backend development, while PostgreSQL provides a powerful and reliable data layer. Together, they form a strong foundation for enterprise and modern Java applications.