If you’re learning backend development, you’ve probably heard of databases like MySQL, MongoDB, and PostgreSQL.
But what exactly is PostgreSQL?
PostgreSQL is a powerful, open-source relational database management system (RDBMS) used to store, organize, and retrieve structured data.
It is widely used for web applications, enterprise software, analytics platforms, APIs, financial systems, and many other types of applications.
PostgreSQL is known for its reliability, powerful SQL support, data integrity, extensibility, and ability to handle complex workloads.
In this beginner-friendly guide, we’ll learn PostgreSQL from the ground up.
We’ll cover:
- What PostgreSQL is
- How PostgreSQL works
- Databases and tables
- Rows and columns
- SQL basics
- Primary keys
- Foreign keys
- Relationships
- CRUD operations
- Joins
- Indexes
- Constraints
- Transactions
- PostgreSQL data types
- PostgreSQL vs MySQL
- PostgreSQL vs MongoDB
- PostgreSQL with Java and Spring Boot
- Common commands
- Best practices
Let’s get started.
What Is PostgreSQL?
PostgreSQL is an open-source relational database system.
It stores data in tables made up of rows and columns.
For example, an application might have a users table:
| id | name | |
|---|---|---|
| 1 | Oliver | oliver@example.com |
| 2 | Sophia | sophia@example.com |
| 3 | Ethan | ethan@example.com |
Each row represents one record.
Each column represents a particular piece of information.
Users
│
├── id
├── name
└── email
Applications can use SQL to insert, update, delete, and retrieve this data.
Why Is PostgreSQL Called a Relational Database?
PostgreSQL is a relational database because data is typically organized into related tables.
For example:
Users
│
└── Orders
│
└── Products
A user might have multiple orders, and each order might contain multiple products.
Relationships between tables allow an application to represent real-world data in an organized way.
PostgreSQL in a Web Application
A typical application might look like this:
Frontend
↓
REST API
↓
Backend Application
↓
PostgreSQL
For example, when a user opens their profile:
Browser
↓
GET /users/101
↓
Backend
↓
PostgreSQL
↓
User Data
↓
JSON Response
PostgreSQL is responsible for storing and retrieving the persistent data.
PostgreSQL vs PostgreSQL Database
It’s useful to understand the terminology.
PostgreSQL is the database management system.
Inside a PostgreSQL server, you can have multiple databases.
For example:
PostgreSQL Server
│
├── ecommerce_db
├── inventory_db
└── analytics_db
Each database can contain its own schemas, tables, views, functions, and other database objects.
What Is a Table?
A table stores structured data.
For example:
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
name VARCHAR(100),
email VARCHAR(255)
);
This creates a table called:
users
with three columns:
id
name
email
You can think of a table like a spreadsheet, but with much stronger rules for storing and relating data.
Rows and Columns
Suppose we have:
users
| id | name | |
|---|---|---|
| 1 | Oliver | oliver@example.com |
| 2 | Sophia | sophia@example.com |
Here:
id,name, andemailare columns.- Each user record is a row.
So:
Column → Type of information
Row → One record
What Is SQL?
SQL stands for Structured Query Language.
It is used to communicate with relational databases.
For example:
SELECT *
FROM users;
This asks PostgreSQL to return all rows from the users table.
SQL is one of the most important skills to learn when working with PostgreSQL.
Creating a Database
PostgreSQL provides SQL commands for creating databases.
For example:
CREATE DATABASE ecommerce;
Now you can connect to the ecommerce database and create tables inside it.
The exact way you connect depends on the PostgreSQL client or tool you’re using.
Creating a Table
Let’s create a simple products table:
CREATE TABLE products (
id BIGSERIAL PRIMARY KEY,
name VARCHAR(150) NOT NULL,
price NUMERIC(10, 2) NOT NULL
);
This creates:
products
│
├── id
├── name
└── price
Inserting Data
To add data, use INSERT.
INSERT INTO products (
name,
price
)
VALUES (
'Laptop',
799.99
);
You can insert multiple records:
INSERT INTO products (
name,
price
)
VALUES
('Keyboard', 49.99),
('Mouse', 29.99),
('Monitor', 249.99);
Reading Data
Use SELECT to retrieve information.
SELECT *
FROM products;
You can select specific columns:
SELECT name, price
FROM products;
You can also filter results.
SELECT *
FROM products
WHERE price > 100;
This returns products whose price is greater than 100.
Updating Data
Use UPDATE to modify existing records.
UPDATE products
SET price = 699.99
WHERE id = 1;
The WHERE clause is extremely important.
Without it:
UPDATE products
SET price = 699.99;
you could accidentally update every row.
Deleting Data
Use DELETE to remove records.
DELETE FROM products
WHERE id = 1;
Again, be careful with WHERE.
This:
DELETE FROM products;
deletes all rows from the table.
CRUD Operations
These four operations are commonly called CRUD:
C → Create
R → Read
U → Update
D → Delete
In SQL:
INSERT → Create
SELECT → Read
UPDATE → Update
DELETE → Delete
Almost every backend application performs CRUD operations.
Primary Key
A primary key uniquely identifies each row in a table.
For example:
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
name VARCHAR(100)
);
Here:
id
↓
Primary Key
Each user gets a unique ID.
For example:
1 → Oliver
2 → Sophia
3 → Ethan
Two rows cannot have the same primary key value.
Why Do We Need Primary Keys?
Imagine a users table containing:
Oliver
Oliver
Sophia
If you search only by name, you may not know which Oliver you’re referring to.
A unique ID solves that problem:
101 → Oliver
102 → Oliver
103 → Sophia
The ID uniquely identifies each record.
Foreign Key
A foreign key connects one table to another.
Suppose we have:
users
and:
orders
The orders table can contain:
CREATE TABLE orders (
id BIGSERIAL PRIMARY KEY,
user_id BIGINT REFERENCES users(id),
total NUMERIC(10, 2)
);
Here:
orders.user_id
↓
users.id
The foreign key establishes a relationship between the tables.
One-to-Many Relationship
A common relationship is:
One user can have many orders.
For example:
Oliver
│
├── Order 101
├── Order 102
└── Order 103
The database can represent this using:
users
↓
id
orders
↓
user_id
This is a one-to-many relationship.
Many-to-Many Relationship
Sometimes one record can be related to many records on both sides.
For example:
Students ↔ Courses
One student can take multiple courses.
One course can have multiple students.
A common relational design uses a junction table:
students
↓
student_courses
↓
courses
For example:
CREATE TABLE student_courses (
student_id BIGINT
REFERENCES students(id),
course_id BIGINT
REFERENCES courses(id),
PRIMARY KEY (
student_id,
course_id
)
);
SQL Joins
Joins allow you to retrieve related data from multiple tables.
Suppose:
users
orders
You can join them:
SELECT
users.name,
orders.total
FROM users
JOIN orders
ON users.id = orders.user_id;
The result might look like:
| name | total |
|---|---|
| Oliver | 299.99 |
| Sophia | 149.99 |
| Oliver | 499.99 |
INNER JOIN
An INNER JOIN returns rows where matching records exist in both tables.
SELECT
u.name,
o.total
FROM users u
INNER JOIN orders o
ON u.id = o.user_id;
Think:
Users
∩
Orders
Only matching records are returned.
LEFT JOIN
A LEFT JOIN returns all rows from the left table, even if there isn’t a matching row on the right.
SELECT
u.name,
o.total
FROM users u
LEFT JOIN orders o
ON u.id = o.user_id;
This can show users who have no orders as well.
Indexes
Indexes help PostgreSQL find data more efficiently.
Suppose you frequently search users by email:
SELECT *
FROM users
WHERE email = 'oliver@example.com';
You might create an index:
CREATE INDEX idx_users_email
ON users(email);
Conceptually:
Without Index
Query
↓
Search many rows
With Index
Query
↓
Index
↓
Matching rows
Indexes can significantly improve read performance for appropriate queries.
Are Indexes Always Good?
No.
Indexes have a cost.
They can:
- Consume storage
- Increase write overhead
- Increase maintenance work
- Slow down
INSERT,UPDATE, andDELETEoperations in some cases
Don’t create indexes on every column.
Create indexes based on actual query patterns and performance requirements.
PostgreSQL Data Types
PostgreSQL supports many data types.
Some common ones are:
Integer
INTEGER
Big Integer
BIGINT
Decimal
NUMERIC
Text
TEXT
Variable-Length String
VARCHAR(100)
Boolean
BOOLEAN
Date
DATE
Timestamp
TIMESTAMP
UUID
UUID
PostgreSQL also provides more specialized types, including arrays, JSON/JSONB, ranges, and other advanced types.
PostgreSQL and JSON
One feature that makes PostgreSQL especially flexible is its support for JSON data.
For example:
CREATE TABLE products (
id BIGSERIAL PRIMARY KEY,
name TEXT,
metadata JSONB
);
You could store:
{
"brand": "NovaTech",
"color": "black",
"features": ["wireless", "compact"]
}
PostgreSQL’s JSONB type is useful when you need semi-structured data while still keeping it inside a relational database.
JSON vs JSONB
PostgreSQL supports both:
JSON
JSONB
JSON stores the JSON representation.
JSONB stores a decomposed binary representation that is generally better for querying and indexing.
For many application use cases where JSON data needs to be queried, JSONB is the more commonly useful choice.
Constraints
Constraints help maintain data integrity.
Common constraints include:
PRIMARY KEYFOREIGN KEYNOT NULLUNIQUECHECK
For example:
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
email VARCHAR(255)
UNIQUE
NOT NULL,
age INTEGER
CHECK (age >= 18)
);
The database can prevent invalid data from being inserted.
NOT NULL
NOT NULL means a column must have a value.
name VARCHAR(100) NOT NULL
This prevents:
name = NULL
when inserting or updating the record.
UNIQUE
UNIQUE prevents duplicate values.
For example:
email VARCHAR(255) UNIQUE
This can ensure that two users cannot have the same email value, subject to PostgreSQL’s rules around NULL values.
CHECK Constraint
A CHECK constraint validates a condition.
For example:
price NUMERIC(10, 2)
CHECK (price >= 0)
Now the database can reject negative prices.
Transactions
Transactions are one of the most important database concepts.
A transaction groups multiple operations into one logical unit.
Imagine transferring money:
Account A
↓
Debit 500
Account B
↓
Credit 500
Both operations should succeed together.
If something goes wrong:
Debit
↓
Failure
the transaction can be rolled back.
ACID Properties
Relational databases such as PostgreSQL support transactions with ACID properties:
A → Atomicity
C → Consistency
I → Isolation
D → Durability
Atomicity
A transaction succeeds as a unit or is rolled back.
Consistency
The database moves from one valid state to another.
Isolation
Concurrent transactions are isolated according to the configured isolation behavior.
Durability
Once committed, changes are designed to survive system failures subject to the database’s durability configuration and storage environment.
PostgreSQL Transactions
A basic transaction looks like:
BEGIN;
UPDATE accounts
SET balance = balance - 500
WHERE id = 101;
UPDATE accounts
SET balance = balance + 500
WHERE id = 102;
COMMIT;
If something goes wrong, you can use:
ROLLBACK;
Transactions are essential for applications where multiple database operations must remain consistent.
PostgreSQL and Concurrency
Multiple users can access a PostgreSQL database at the same time.
For example:
User A ──┐
User B ──┼──→ PostgreSQL
User C ──┤
User D ──┘
PostgreSQL uses MVCC (Multi-Version Concurrency Control) to help manage concurrent transactions.
This allows readers and writers to work concurrently without every operation requiring a simple global lock.
Understanding transactions and isolation becomes increasingly important as applications grow.
PostgreSQL Schemas
A PostgreSQL database can contain multiple schemas.
For example:
ecommerce
│
├── public
├── reporting
└── internal
A schema provides a namespace for database objects.
For example:
CREATE SCHEMA reporting;
You can then create objects inside it:
CREATE TABLE reporting.monthly_sales (
month DATE,
total NUMERIC(12, 2)
);
Schemas can be useful for organizing database objects and controlling access.
Views
A view is a stored query that can be queried like a table.
For example:
CREATE VIEW active_users AS
SELECT id, name, email
FROM users
WHERE active = true;
Then:
SELECT *
FROM active_users;
Views can simplify repeated queries and provide controlled access to underlying data.
PostgreSQL Functions
PostgreSQL also supports functions that can execute logic inside the database.
For example, PostgreSQL supports SQL functions and procedural languages such as PL/pgSQL.
A simple function might look like:
CREATE FUNCTION add_numbers(
a INTEGER,
b INTEGER
)
RETURNS INTEGER
LANGUAGE SQL
AS $$
SELECT a + b;
$$;
Then:
SELECT add_numbers(10, 20);
returns:
30
Database functions can be useful, but business logic should be placed thoughtfully rather than automatically moved into the database.
PostgreSQL with Java
If you’re learning Java backend development, PostgreSQL is an excellent database to learn alongside Java.
A common stack is:
Java
↓
Spring Boot
↓
Spring Data JPA
↓
Hibernate
↓
JDBC Driver
↓
PostgreSQL
The application can use JPA/Hibernate for object-relational mapping while PostgreSQL handles persistent data storage.
PostgreSQL with Spring Boot
A Spring Boot application can connect to PostgreSQL using the PostgreSQL JDBC driver and Spring Data JPA.
A typical configuration might look like:
spring.datasource.url=jdbc:postgresql://localhost:5432/ecommerce
spring.datasource.username=postgres
spring.datasource.password=your_password
In a real application, don’t hard-code sensitive credentials in source code.
Use environment variables or a secure configuration system.
Example Spring Boot Entity
Suppose we have:
@Entity
public class User {
@Id
@GeneratedValue
private Long id;
private String name;
private String email;
}
Spring Data JPA can map this entity to a PostgreSQL table.
You can then create a repository:
public interface UserRepository
extends JpaRepository<User, Long> {
}
The general flow becomes:
Java Object
↓
JPA / Hibernate
↓
JDBC
↓
PostgreSQL
PostgreSQL vs MySQL
Both PostgreSQL and MySQL are popular relational databases.
| Feature | PostgreSQL | MySQL |
|---|---|---|
| Type | Relational | Relational |
| Open Source | Yes | Yes |
| SQL Support | Very strong | Very strong |
| Complex Queries | Excellent | Excellent |
| JSON Support | Excellent | Good |
| Extensibility | Very strong | Strong |
| Advanced Data Types | Extensive | Good |
| Enterprise Usage | Very common | Very common |
| Best Choice | Depends on requirements | Depends on requirements |
It’s difficult to declare one universally better.
The right choice depends on:
- Application requirements
- Existing infrastructure
- Team experience
- Database features needed
- Hosting environment
- Performance characteristics
PostgreSQL vs MongoDB
PostgreSQL and MongoDB represent different database approaches.
PostgreSQL
Relational:
Tables
↓
Rows
↓
Relationships
MongoDB
Document-oriented:
Collection
↓
Documents
↓
JSON-like data
PostgreSQL is often a strong choice when you need:
- Complex relationships
- Transactions
- Strong relational integrity
- Complex SQL queries
- Structured data
MongoDB can be useful when document-oriented modeling is a better fit.
The choice should be based on the data model and application requirements, not simply on popularity.
Why Developers Choose PostgreSQL
PostgreSQL has several important strengths.
Open Source
It can be used without proprietary database licensing fees.
Strong SQL Support
It provides a rich SQL implementation.
Data Integrity
Constraints and transactional behavior help protect data quality.
Extensibility
PostgreSQL supports extensions, custom types, functions, and other advanced capabilities.
Advanced Features
It supports features such as:
- Window functions
- Common table expressions
- JSONB
- Full-text search
- Arrays
- Range types
- Materialized views
- Partitioning
- Replication features
Strong Community
PostgreSQL has a large global community and extensive documentation.
PostgreSQL Performance
PostgreSQL can handle anything from small applications to large production workloads.
Performance depends on many factors, including:
Database Design
↓
Indexes
↓
Query Efficiency
↓
Connection Pooling
↓
Hardware
↓
Caching
↓
Application Architecture
Simply choosing PostgreSQL doesn’t automatically make an application fast.
Poor queries can still be slow.
Query Optimization
Suppose you have:
SELECT *
FROM orders
WHERE user_id = 101;
If the table contains millions of rows, an appropriate index on user_id may improve the query.
You can investigate query plans using:
EXPLAIN
or:
EXPLAIN ANALYZE
For example:
EXPLAIN ANALYZE
SELECT *
FROM orders
WHERE user_id = 101;
This helps developers understand how PostgreSQL executes a query.
Connection Pooling
Applications don’t usually want to create a brand-new database connection for every request.
Instead, they often use a connection pool.
Conceptually:
Application
↓
Connection Pool
┌───┼───┬───┐
C1 C2 C3 C4
↓
PostgreSQL
A pool reuses database connections.
In Spring Boot applications, connection pooling is commonly handled by libraries such as HikariCP.
Backups
Database backups are essential for production systems.
A good database strategy should consider:
- Regular backups
- Backup retention
- Recovery procedures
- Point-in-time recovery where appropriate
- Disaster recovery
- Testing restoration
A backup that has never been tested isn’t a reliable recovery strategy.
PostgreSQL Security
Database security is extremely important.
Important practices include:
Strong Authentication
Use secure credentials and appropriate authentication mechanisms.
Least Privilege
Give users and applications only the permissions they need.
Network Security
Don’t expose a production database unnecessarily to the public internet.
Encrypted Connections
Use TLS/SSL where appropriate.
Secure Secrets
Don’t commit database passwords to Git repositories.
Regular Updates
Keep PostgreSQL and its dependencies appropriately maintained.
Common PostgreSQL Commands
If you’re using the PostgreSQL command-line client, you’ll encounter commands such as:
\l
Lists databases.
\c database_name
Connects to a database.
\dt
Lists tables.
\d users
Shows information about a table.
\dn
Lists schemas.
\q
Exits the PostgreSQL client.
These commands are specific to the psql client rather than SQL itself.
Basic PostgreSQL Workflow
A typical beginner workflow looks like:
Create Database
↓
Create Tables
↓
Define Constraints
↓
Insert Data
↓
Query Data
↓
Create Indexes
↓
Connect Application
↓
Monitor & Optimize
This is a useful process to understand before moving into advanced PostgreSQL topics.
Common Mistakes Beginners Make
1. Forgetting WHERE
Be careful with:
UPDATE users
SET name = 'Oliver';
This updates every row.
Likewise:
DELETE FROM users;
deletes every row.
Always understand exactly which rows a query will affect.
2. Creating Too Many Indexes
Indexes aren’t free.
Too many indexes can increase storage requirements and write overhead.
3. Storing Everything as Text
Don’t use:
price TEXT
when the value represents a number.
Use an appropriate numeric type.
Good data types improve correctness and query behavior.
4. Ignoring Constraints
Application validation is useful, but important data integrity rules should often also be enforced at the database level.
5. Not Using Transactions
If multiple operations must succeed together, consider whether they belong in one transaction.
6. Using SELECT * Everywhere
Instead of:
SELECT *
FROM users;
consider selecting only the columns you need:
SELECT id, name, email
FROM users;
This can make queries clearer and reduce unnecessary data transfer.
PostgreSQL Learning Roadmap
If you’re completely new to PostgreSQL, learn it in this order:
SQL Basics
↓
Databases & Tables
↓
CRUD
↓
Primary Keys
↓
Foreign Keys
↓
Relationships
↓
Joins
↓
Constraints
↓
Indexes
↓
Transactions
↓
Query Optimization
↓
PostgreSQL Advanced Features
Then learn how to connect PostgreSQL with your preferred backend technology.
For Java developers:
PostgreSQL
↓
JDBC
↓
JPA
↓
Hibernate
↓
Spring Data JPA
↓
Spring Boot
PostgreSQL Cheat Sheet
Here are some essential commands to remember.
Create Database
CREATE DATABASE ecommerce;
Create Table
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
name TEXT NOT NULL
);
Insert
INSERT INTO users (name)
VALUES ('Oliver');
Read
SELECT *
FROM users;
Update
UPDATE users
SET name = 'Sophia'
WHERE id = 1;
Delete
DELETE FROM users
WHERE id = 1;
Add Index
CREATE INDEX idx_users_name
ON users(name);
Start Transaction
BEGIN;
Commit
COMMIT;
Rollback
ROLLBACK;
Final Thoughts
PostgreSQL is much more than a place to store rows of data.
It provides a powerful platform for building reliable applications with:
SQL
+
Relationships
+
Transactions
+
Constraints
+
Indexes
+
JSONB
+
Advanced Queries
+
Concurrency
+
Extensibility
For a beginner, don’t try to learn every PostgreSQL feature at once.
Start with the fundamentals:
tables → CRUD → keys → relationships → joins → indexes → transactions.
Once those concepts are comfortable, move into query optimization, JSONB, partitioning, advanced indexing, replication, and PostgreSQL administration.
If you’re learning backend development with Java and Spring Boot, PostgreSQL is especially valuable because it fits naturally into a modern backend stack:
Spring Boot
↓
JPA / Hibernate
↓
JDBC
↓
PostgreSQL
The most important lesson is simple:
Good database design is just as important as good application code.
Learn PostgreSQL properly, understand why your queries work, design your relationships carefully, and your backend development skills will become much stronger.
