PostgreSQL Tutorial

PostgreSQL is an open-source, object-relational database management system (ORDBMS) that uses and extends SQL to store, manage, and retrieve structured data. It is known for its reliability, scalability, and advanced features such as:

• Support for complex queries
• Transactions
• JSONB storage
• Custom data types
• High concurrency through Multi-Version Concurrency Control (MVCC).

Nowadays, many big tech companies including Apple, Instagram, Netflix and Uber have also adopted PostgreSQL for their certain workloads.

While MySQL is simpler and efficient for read-heavy, lightweight web applications, PostgreSQL excels in enterprise-grade environments where scalability, complex data modeling, and reliability are critical. Its support for multiple index types, advanced query planner, and extensibility through custom functions and extensions (like PostGIS for geospatial data) make it far more versatile.

Writing Your First SQL Query in PostgreSQL

Below is an example to display “Hello, World!” using SQL:

1. Create a database

CREATE DATABASE test_db;

2. Connect to the database

\c test_db;

3. Create a table

CREATE TABLE greetings (
    id SERIAL PRIMARY KEY,
    message VARCHAR(255)
);

4. Insert a message

INSERT INTO greetings (message)
VALUES ('Hello, World!');

5. Retrieve the message

SELECT message FROM greetings;

Output

Note: Try replacing “Hello, World!” with your own name in the INSERT statement to see how PostgreSQL stores and displays it!

PostgreSQL Basics

Here in this section you will learn introduction of PostgreSQL, how to install PostgreSQL on various OS and other PostgreSQL basics.

Before starting to learn PostgreSQL we need to install PostgreSQL on our system.

• Introduction
• Loading a Database
• Create Database
• ALTER DATABASE
• DROP DATABASE
• Rename Database
• Copy Database
• Size of a Database
• Show Databases

Data Types

Data types in PostgreSQL define the kind of values you can store in a column, such as numbers, text, dates, or JSON. In this section, we cover the commonly used built-in types along with special ones like arrays, hstore, and user-defined types.

• Data Types
• Boolean Data Type
• CHAR Data Type
• VARCHAR Data Type
• TEXT Data Type
• NUMERIC Data Type
• SMALLINT Integer Data Type
• INTEGER Data Type
• BIGINT Integer Data Type
• Date Data Type
• Timestamp Data Type.
• UUID Data Type
• TIME Data Type
• Interval Data Type
• User-defined Data Type
• Array Data Type
• hstore Data Type
• JSON Data Type

Querying & Filtering Data

Querying and filtering in PostgreSQL is used to fetch specific data from tables based on conditions. In this section, we cover SELECT statements, filtering with WHERE, sorting, grouping, and using operators like IN, LIKE, and BETWEEN.

• SELECT
• SELECT DISTINCT clause
• ORDER BY clause
• WHERE clause
• LIMIT clause
• FETCH clause
• IN operator
• IS NULL operator
• LIKE operator
• NOT LIKE operator
• BETWEEN operator
• HAVING clause
• GROUP BY clause

Managing Tables

Tables in PostgreSQL store data in rows and columns, and managing them involves creating, modifying, and removing structures. In this section, we cover creating tables, altering columns, renaming, truncating, temporary tables, and importing data.

• CREATE TABLE
• SELECT INTO
• Create Auto-increment Column using SERIAL
• CREATE SEQUENCE
• Identity Column
• ALTER TABLE
• Rename Table
• ADD COLUMN
• DROP COLUMN
• Change Column Type
• RENAME COLUMN
• DROP TABLE
• TRUNCATE TABLE
• Temporary Table
• Temporary table name
• Removing Temporary Table
• Copy a Table
• Comparing Tables
• Describe Table
• Show Tables
• Import CSV File Into Table

Modifying Data

Modifying data in PostgreSQL means adding, changing, or removing records in a table. In this section, we cover inserting rows, updating values, deleting records, and handling upserts.

• INSERT
• Insert multiple rows
• UPDATE
• DELETE
• Upsert

Conditionals

Conditionals in PostgreSQL help control query results by handling choices, null values, and type conversions. In this section, we cover CASE, COALESCE, NULLIF, and CAST.

• CASE
• COALESCE
• NULLIF() Function
• CAST

Control Flow

Control flow in PostgreSQL lets you manage the execution of statements using conditions and loops. In this section, we cover IF, CASE, loops, EXIT, and CONTINUE.

• IF Statement
• CASE Statement
• Loop Statement
• While Loops
• For Loops
• Exit
• Continue

Transactions & Constraints

Transactions and constraints in PostgreSQL ensure data reliability and integrity. In this section, we cover starting and managing transactions along with key constraints like PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, and NOT NULL.

• Transactions
• COMMIT
• BEGIN
• ROLLBACK
• Primary Key
• Foreign Key
• CHECK Constraint
• UNIQUE Constraint
• NOT NULL Constraint

Working with JOINS & Schemas

Joins in PostgreSQL combine data from multiple tables, while schemas help organize database objects. In this section, we cover different JOIN types along with creating, altering, and dropping schemas.

• Joins
• LEFT JOIN
• INNER JOIN
• FULL OUTER JOIN
• SELF JOIN
• Schema
• CREATE SCHEMA
• DROP SCHEMA
• ALTER SCHEMA

Roles & Permissions

Roles and permissions in PostgreSQL control user access and security. In this section, we cover creating, altering, and dropping roles, along with granting, revoking, and managing role memberships.

• CREATE ROLE
• ALTER ROLE
• DROP ROLE
• GRANT
• REVOKE
• Role Membership

Working with Sets

Working with sets in PostgreSQL allows combining and comparing query results. In this section, we cover UNION, INTERSECT, EXCEPT, and advanced grouping operations like GROUPING SETS, CUBE, and ROLLUP.

• UNION operator
• INTERSECT Operator
• EXCEPT Operator
• GROUPING SETS
• CUBE
• ROLLUP

Subquery & CTEs

Subqueries and CTEs in PostgreSQL let you build complex queries by nesting or reusing result sets. In this section, we cover operators like ANY, ALL, EXISTS, using CTEs, and practical cases like removing duplicates.

• ANY Operator
• ALL Operator
• EXISTS Operator
• CTE
• Deleting Duplicate Rows using Subquery

User-Defined Functions

User-defined functions in PostgreSQL let you create reusable logic for queries. In this section, we cover creating functions, parameter modes, overloading, returning tables, and dropping functions.

• CREATE FUNCTION Statement
• Function parameter modes
• Function Overloading
• Function that returns table
• Drop Function

Important In-Built Functions

PostgreSQL provides many built-in functions to simplify data analysis and manipulation. In this section, we cover aggregate, window, date/time, string, and regex functions commonly used in queries.

• AVG() Function
• COUNT() Function
• MAX() Function
• MIN() Function
• SUM() Function
• FIRST_VALUE Function
• LAST_VALUE Function
• NTH_VALUE Function
• ROW_NUMBER Function
• CURRENT_DATE Function
• CURRENT_TIME Function
• EXTRACT Function
• CONCAT Function
• FORMAT Function
• UPPER function
• LOWER function
• REGEXP_MATCHES Function
• REGEXP_REPLACE Function
• REPLACE Function

Visit PostgreSQL In-Built functions for more.

Advanced PostgreSQL Tutorial

In this section, you'll learn about advanced features of PostgreSQL that can help you manage your databases more efficiently. We'll cover topics like performance tuning, indexing strategies, and using advanced SQL functions. You'll also explore how to handle large datasets, optimize queries, and set up replication for high availability.

PostgreSQL PL/pgSQL

PL/pgSQL is PostgreSQL’s procedural language that adds programming features to SQL. In this section, we cover dollar-quoted string constants and the basic block structure.

• Dollar-Quoted String Constants
• Block Structure

Variables & Constants

Variables and constants in PostgreSQL PL/pgSQL store data temporarily for use in procedures and functions. In this section, we cover different variable types, SELECT INTO usage, and defining constants.

• Variables
• Select Into
• Row type variables
• Record type variable
• Constants

Stored Procedures

Stored procedures in PostgreSQL are reusable blocks of code that perform tasks without returning data. In this section, we cover their introduction, creation, and deletion.

• Introduction to Stored Procedures
• CREATE PROCEDURE
• Drop Procedure

Working with Triggers

Triggers in PostgreSQL are actions that run automatically when certain events occur on a table. In this section, we cover creating, altering, enabling, disabling, and dropping triggers.

• Trigger
• CREATE TRIGGER
• DROP TRIGGER
• ALTER TRIGGER
• Disabling a Trigger
• Enabling a Trigger

Working with Views & Indexes

Views and indexes in PostgreSQL improve data access and performance. In this section, we cover creating and managing indexes, unique and partial indexes, expression-based indexes, and reindexing

• CREATE INDEX
• DROP INDEX
• List Indexes
• UNIQUE Index
• Partial Index
• Index On Expression
• REINDEX
• Multicolumn Indexes

Errors & Exception Handling

Error and exception handling in PostgreSQL helps manage unexpected situations during execution. In this section, we cover system messages, handling exceptions, and using ASSERT statements.

• Errors and Messages
• Exception Handling
• Assert

Exercises, Interview Questions & Cheat Sheet

This section offers practical exercises and commonly asked interview questions to help strengthen your PostgreSQL skills. It also includes a cheat sheet for quick reference, making PostgreSQL concepts easier to understand and apply.

• PostgreSQL Exercises
• PostgreSQL Interview Questions and Answers
• PostgreSQL - Cheat Sheet : Basic to Advanced

PostgreSQL Vs MySQL

Here are the detailed difference between PostgreSQL and MySQL:

Type

• PostgreSQL: Object-relational database
• MySQL: Relational database

ACID Compliance

• PostgreSQL: Fully ACID compliant
• MySQL: Fully ACID compliant

Complex Queries

• PostgreSQL: Excellent support for complex queries (CTEs, window functions, recursive queries)
• MySQL: Good support, but less advanced compared to PostgreSQL

Data Types

• PostgreSQL: Wide range of advanced types (arrays, hstore, JSONB, UUID, custom types)
• MySQL: Limited/basic set of types

JSON Support

• PostgreSQL: Strong support with JSON/JSONB, indexing, and querying
• MySQL: Good support, but less efficient for large-scale JSON operations

Performance

• PostgreSQL: Great for complex, read-intensive and analytic operations
• MySQL: Fast for simple read-heavy and write-heavy web workloads

Extensibility

• PostgreSQL: Highly extensible (custom functions, data types, extensions like PostGIS)
• MySQL: Limited extensibility

Replication

• PostgreSQL: Supports multiple replication methods (streaming, logical, synchronous)
• MySQL: Primarily master-slave replication (though newer versions support group replication)

Community & Support

• PostgreSQL: Strong, highly active developer community
• MySQL: Strong, very widely used and supported globally

Usage

• PostgreSQL: Preferred for enterprise, fintech, analytics, geospatial, and complex applications
• MySQL: Preferred for websites, CMSs, and lightweight web applications

License

• PostgreSQL: Open-source (PostgreSQL License – very permissive)
• MySQL: Open-source (GPL License, with Oracle’s commercial influence