In this video 📺, we explore Mathematical Functions and Operators in PostgreSQL in depth. PostgreSQL provides a wide range of built-in tools that make complex calculations easy to perform directly inside your SQL queries.
We’ll cover everything step by step with examples and demos, including:
✅ Arithmetic operators (+, -, *, /, %, ^)
✅ Absolute value, square root, cube root, power
✅ Rounding, truncation, logarithmic & exponential functions
✅ Factorials, GCD, LCM, and PI
✅ Random number generation and seeding
✅ Trigonometric functions (sin, cos, tan, atan2) in radians & degrees
✅ Hyperbolic functions (sinh, cosh, tanh, etc.)
By the end of this session, you’ll know how to use these functions in real-world cases like financial applications, GIS, scientific computations, and simulations. 🚀
👉 This is part of the PostgreSQL Full Playlist. Don’t forget to check out previous episodes to build a strong foundation!
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In this video, we’ll dive into Comparison Functions and Operators in PostgreSQL. These are essential for writing precise queries, handling null values, and performing safe comparisons in your database applications.
You’ll learn:
Basic comparison operators (<, >, =, <>, !=)
Range testing with BETWEEN and NOT BETWEEN
Using BETWEEN SYMMETRIC for unordered ranges
NULL-safe comparisons with IS DISTINCT FROM and IS NOT DISTINCT FROM
Checking for missing data with IS NULL, IS NOT NULL, and alternatives
Boolean checks like IS TRUE, IS FALSE, and IS UNKNOWN
Row-level null comparisons and their tricky behavior
Handy functions like num_nulls() and num_nonnulls() for analyzing null values
We’ll also cover best practices, pitfalls, and performance tips to ensure your queries run efficiently while avoiding common mistakes with null handling and cross-type comparisons.
📌 This is part of the PostgreSQL Full Playlist, so make sure to check out the other videos if you want to master PostgreSQL step by step.
In this video, we dive into Logical Operators in PostgreSQL, an essential part of writing powerful and efficient queries. Logical operators help us combine multiple conditions and make decisions in our SQL statements.
We’ll cover the three main operators — AND, OR, and NOT — along with PostgreSQL’s three-valued logic system (TRUE, FALSE, and NULL). You’ll also learn how these operators work through truth tables and practical examples using an employees table.
📌 What you’ll learn in this video:
Introduction to PostgreSQL Logical Operators
Detailed explanation of AND, OR, and NOT
How NULL affects logical operations
Using logical operators in WHERE clauses
Real-world examples with CREATE TABLE and INSERT statements
By the end of this tutorial, you’ll have a strong understanding of how logical operators work in PostgreSQL, enabling you to write more accurate and efficient queries.
👉 Don’t forget to check out the Full PostgreSQL Playlist for a complete step-by-step guide on mastering PostgreSQL.
Welcome to Part 55 of our PostgreSQL Full Playlist! 🎥 In this video, we dive deep into one of the most powerful data types in PostgreSQL — JSON and JSONB.
📌 What You’ll Learn:
The difference between json and jsonb types
How PostgreSQL stores and processes JSON data
Practical examples: inserting, querying, and updating JSON fields
Using operators like @>, ?, and ->>
Powerful indexing strategies using GIN, BTREE, and expression indexes
Working with jsonpath queries for complex lookups
Handling edge cases like Unicode, nulls, and nested structures
Real-world best practices and performance tips for working with semi-structured data
PostgreSQL’s support for JSON is incredibly robust, allowing developers to handle flexible data formats while still benefiting from SQL power.
Whether you're a backend developer, database admin, or student, this video will equip you with essential skills for modern data modeling using JSON in PostgreSQL.
📚 Don’t forget to check the full playlist for more videos on PostgreSQL indexing, constraints, normalization, functions, and performance tuning!
✅ Subscribe, Like, Comment & Share to support the channel and stay updated with the latest tutorials.
Welcome to Episode #51 of our PostgreSQL Full Playlist! 🎬
In this tutorial, we dive deep into Bit String Data Types in PostgreSQL—BIT(n) and BIT VARYING(n). These types allow you to store and manipulate binary sequences (1s and 0s), perfect for compact data storage like bitmasks, feature flags, and permission sets.
We’ll cover:
What are BIT(n) and BIT VARYING(n) types?
The difference between fixed and variable-length bit strings
How to insert valid/invalid values
How casting affects storage (padding and truncation)
Real-world use cases
Using bitwise operators (AND, OR, XOR, NOT)
Useful bit string functions like LENGTH() and OCTET_LENGTH()
Common pitfalls and advanced tips
With full examples and clear explanations, this video is ideal for both beginners and intermediate PostgreSQL learners.
📌 Don't forget to:
👍 Like | 💬 Comment | 🔔 Subscribe | 📂 Watch the full playlist for more PostgreSQL concepts!
In this video, we explore Network Address Data Types in PostgreSQL — an essential part of working with IP addresses and MAC addresses directly in the database.
You’ll learn how PostgreSQL provides specialized support for IP address types such as inet (IPv4/IPv6 hosts), cidr (network blocks), and MAC address formats like macaddr and macaddr8. These data types are far more reliable and efficient than storing IPs as plain text, allowing for input validation, indexing, subnetting operations, and more.
We also provide practical examples, including:
Creating tables using inet, cidr, macaddr, and macaddr8
Inserting and querying IP and MAC addresses
Using powerful built-in functions like host(), netmask(), abbrev(), and macaddr8_set7bit()
Understanding the difference between inet and cidr
If you're building applications involving network infrastructure, IoT devices, firewalls, or logging systems — this tutorial is a must-watch!
📌 Full Playlist: Don’t forget to check out the complete PostgreSQL series if you’re following along from the start.
Welcome to Episode 49 of the PostgreSQL Full Playlist! In this tutorial, we explore one of the most important areas of database development — Date/Time and Interval Data Types in PostgreSQL.
PostgreSQL provides highly flexible and powerful temporal data types including DATE, TIME, TIMESTAMP, TIMESTAMPTZ, and INTERVAL. Whether you're handling simple dates, calculating durations, or dealing with timezone-aware timestamps, this video will guide you through all the critical concepts with real-world use cases, hands-on SQL examples, and expert-level insights.
You will learn:
The difference between TIMESTAMP and TIMESTAMPTZ
How to use and format INTERVAL for date arithmetic
How time zone conversion works using AT TIME ZONE
Date formatting with datestyle and intervalstyle
Special constants like now, epoch, today, and yesterday
Functions like CURRENT_DATE, DATE_TRUNC, EXTRACT, and more!
💡 This video is perfect for:
Students learning databases
Backend developers handling temporal data
Data engineers dealing with time-series data
Anyone preparing for SQL interviews or certifications
👉 Don’t forget to LIKE, SUBSCRIBE, and SHARE if you find this helpful. Drop your questions or feedback in the comments — I’d love to help out!
🔔 Subscribe for more PostgreSQL and Database tutorials.
Welcome to Video #46 in our PostgreSQL Full Playlist! 🎥
In this video, we dive deep into one of the most essential data types in PostgreSQL — the Boolean Data Type. Learn how PostgreSQL handles binary logic with TRUE, FALSE, and NULL (unknown) values. We’ll walk through how to declare Boolean fields, accepted input formats (like yes, 1, off, etc.), and demonstrate real-world use cases like tracking product availability, student enrollment, and user activity statuses.
You'll also learn:
The internal storage and behavior of booleans in PostgreSQL.
SQL-standard vs. alternate representations ('1', 'no', 'yes', etc.).
How NULL behaves differently and when to cast it explicitly.
Writing smart queries using WHERE clauses for TRUE, FALSE, and NULL values.
Whether you're preparing for interviews, building applications, or just exploring PostgreSQL, this video will give you the practical knowledge you need.
👉 Don’t forget to Like, Share, and Subscribe for the complete playlist!
In this video, we dive deep into Common Table Expressions (CTEs) in PostgreSQL — a powerful feature that helps you write cleaner, more modular, and efficient SQL queries.
Whether you're a beginner exploring PostgreSQL or an advanced user refining your skills, this tutorial covers everything you need to know about WITH queries, including:
✅ What is a CTE?
✅ Syntax and structure
✅ Benefits of using CTEs
✅ Simple CTEs for temporary data sets
✅ Recursive CTEs for generating sequences or traversing hierarchies
✅ Data-Modifying CTEs using INSERT, UPDATE, and DELETE
✅ Using CTEs with JOINs to simplify complex multi-table queries
✅ Materialization and performance tips
You'll see real-time PostgreSQL examples that demonstrate how CTEs can be applied to real-world scenarios like summarizing data, cleaning up subqueries, and chaining modifications.
📌 This video is part of our PostgreSQL Full Playlist, where we guide you step-by-step from basic concepts to advanced performance optimizations.
💡 Don’t forget to like, comment, and subscribe to stay updated with more database content!
In this video of our PostgreSQL Full Playlist (#41), we take a deep dive into the VALUES clause—a powerful feature that lets you define temporary constant row sets without creating a real table.
We cover a variety of real-world scenarios, including:
Basic usage of the VALUES clause
Assigning column aliases
Using VALUES in INSERT statements (single and multiple rows)
Joining VALUES with real tables in the FROM clause
Performing bulk updates using VALUES and UPDATE together
Working with type casting, such as filtering IP addresses
Sorting and slicing result sets using ORDER BY, LIMIT, and OFFSET
Each example is practical, beginner-friendly, and designed to help you build solid SQL skills in PostgreSQL. Whether you're prepping for an interview or strengthening your database knowledge, this tutorial has something for everyone.
🔔 Don’t forget to like, comment, and subscribe to the channel for more hands-on PostgreSQL content.
Welcome to video #39 in our PostgreSQL Full Playlist! 🎬 In this tutorial, we dive deep into one of the most essential clauses in SQL: the ORDER BY clause.
You'll learn how to sort query results in PostgreSQL based on one or more columns, expressions, and aliases. We also explain how to handle NULL values using NULLS FIRST and NULLS LAST, sort using column positions, and apply ORDER BY in advanced cases such as UNION, CTEs, and window functions.
Whether you're preparing for interviews, writing production queries, or optimizing reports and dashboards, understanding ORDER BY is critical for clear and consistent output.
We demonstrate everything with real examples and walkthroughs, using a practical employees table. This lesson also includes tips on performance, index use, and sorting text data with collation.
🎯 Topics Covered:
Basic ascending and descending sorting
Sorting by expressions like salary + bonus
Handling NULLs explicitly
Using column aliases and positions in ORDER BY
ORDER BY with UNION, DISTINCT, and LIMIT/OFFSET
Sorting randomly with RANDOM()
Analytical queries using RANK() with OVER
Performance tips using EXPLAIN
Make sure to subscribe and check out the full PostgreSQL series for complete mastery! 🚀
📌 Stay tuned for the next episode: LIMIT and OFFSET in PostgreSQL Queries
🔍 Welcome to the Ultimate PostgreSQL Tutorial Series!
In this video (#37), we dive deep into one of the most crucial parts of any SQL query—the SELECT list. Whether you're a beginner or brushing up your database skills, this tutorial will guide you through the many ways PostgreSQL lets you customize the data you retrieve.
👨💻 What You'll Learn:
How to select all or specific columns
Using table aliases for cleaner queries
Creating computed columns with expressions
Renaming outputs with column aliases (AS)
Eliminating duplicates with DISTINCT and DISTINCT ON
Leveraging subqueries, functions, and CASE expressions
Working with JSON, arrays, and aggregate functions
Using LIMIT, OFFSET, and even SELECT without a FROM clause
Advanced techniques like CTEs (Common Table Expressions)
✨ With practical examples, best practices, and performance tips, this tutorial is your go-to guide for mastering SELECT lists in PostgreSQL!
🧠 Next Video: Combining Queries in PostgreSQL – UNION, INTERSECT, EXCEPT
👍 Don't forget to like, subscribe, and turn on notifications for more powerful PostgreSQL lessons.
Welcome to another power-packed tutorial in our PostgreSQL series! 🚀 In Video #36, we dive deep into the world of Window Functions in PostgreSQL — an essential tool for writing analytical queries without losing row-level detail.
💡 Unlike regular aggregate functions, window functions let you calculate SUM, AVG, RANK, ROW_NUMBER, and moving averages over partitions of data while keeping every row visible. This opens up possibilities for advanced reporting, analytics, and insights directly within your SQL.
📊 We walk through real-world use cases with a sales table, showing step-by-step how to:
Calculate running totals and moving averages
Assign rankings and row numbers
Use LEAD and LAG for accessing prior/next rows
Work with PARTITION BY, ORDER BY, ROWS BETWEEN, and RANGE BETWEEN
Optimize performance with shared window specs and indexing tips
We even explore NTILE bucketing, filtered aggregations, and how to use GROUP BY alongside window functions.
Whether you're preparing for interviews, working on a data project, or just want to level up your SQL skills — this tutorial is packed with everything you need!
👉 Don’t forget to subscribe, like, and share if you find this helpful. Drop your questions in the comments, and stay tuned for the next video on Select Lists in PostgreSQL.
Master the GROUP BY and HAVING clauses in PostgreSQL with real-world examples! 🚀
In this tutorial, we explore how GROUP BY helps in summarizing data and how HAVING filters the grouped results. These SQL clauses are crucial for data analysis, reporting, and decision-making.
🔹 What You’ll Learn in This Video?
✔️ How GROUP BY organizes data into meaningful groups
✔️ Using aggregate functions like SUM(), COUNT(), AVG() with GROUP BY
✔️ Applying HAVING to filter grouped results
✔️ Practical examples with employee salary analysis & online order revenue calculations
💻 Example Queries Used in This Video:
📌 Employee Salary Analysis
Calculate total salary per department
Count employees in each department
📌 Online Orders Revenue Analysis
Find total revenue per product
Filter high-revenue products using HAVING
📚 Sample Query – Total Revenue per Product
SELECT product, SUM(quantity * price) AS total_revenue
FROM orders
GROUP BY product;
🔥 Ready to level up your SQL skills? Watch the full tutorial and practice along!
📢 Next Video: GROUPING SETS, CUBE, and ROLLUP in PostgreSQL
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Managing dependencies in PostgreSQL is crucial for maintaining database integrity. In this tutorial, we explore how PostgreSQL tracks dependent objects and prevents accidental deletions.
🔹 Understanding Dependency Tracking
PostgreSQL ensures that if an object (like a table, function, or type) has dependencies, it cannot be dropped unless explicitly handled. This mechanism prevents orphaned objects and data inconsistencies.
🔹 Foreign Key Dependency Example
Consider a products table and an orders table where orders.product_no references products.product_id. If we attempt to drop the products table, PostgreSQL throws an error, warning us about the foreign key constraint.
🔹 Using CASCADE and RESTRICT
CASCADE: Automatically removes all dependent objects when dropping a parent object.
RESTRICT: Prevents dropping an object if dependencies exist, ensuring safe deletion.
🔹 Function and Type Dependencies
Functions can depend on tables and types. PostgreSQL tracks dependencies for types but may not track tables unless the function is written in a SQL-standard format using BEGIN ATOMIC. Dropping a type will force PostgreSQL to remove dependent functions.
🔹 Best Practices
✅ Always check dependencies before dropping objects.
✅ Use CASCADE with caution to avoid unintended deletions.
✅ Write SQL-standard functions if table dependencies need tracking.
Watch the full video to see practical demonstrations and error-handling strategies in PostgreSQL! 🚀
📌 Next Up: Data Manipulation in PostgreSQL – Inserting Data
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PostgreSQL supports table inheritance, a powerful feature that allows tables to inherit structure and data from other tables. This enables database designers to model complex real-world relationships efficiently.
🔹 Understanding PostgreSQL Inheritance Inheritance in PostgreSQL allows a child table to automatically acquire the columns of a parent table. This is useful for scenarios where multiple tables share common attributes but also require unique fields.
🔹 Basic Example: Cities and Capitals We demonstrate how a capitals table can inherit from a cities table, making data retrieval more streamlined. Queries on the parent table can include data from child tables, but you can also filter specific tables using the ONLY keyword.
🔹 Querying Inherited Data
Retrieve all records (including inherited rows)
Query only parent table records using ONLY
Identify source tables using the tableoid system column
🔹 Limitations & Constraints While CHECK and NOT NULL constraints are inherited, primary keys, unique constraints, and foreign keys are not. This video explores how to work around these limitations effectively.
🔹 Advanced Inheritance Features
Multiple Inheritance – A table can inherit from multiple parent tables, merging attributes from all.
Dynamic Inheritance – Modify inheritance relationships on the fly using ALTER TABLE.
Dropping Parent Tables – Child tables must be handled carefully before dropping a parent table.
🔹 Real-World Applications We explore practical use cases where inheritance simplifies schema design, improves query performance, and enhances access control.
📌 Conclusion PostgreSQL inheritance is a flexible tool for organizing database schemas, but it has limitations regarding constraints, indexing, and insert behavior. Understanding these aspects will help you design efficient and scalable databases.
🚀 Next Topic:Table Partitioning in PostgreSQL – Stay tuned!
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Welcome to another informative episode of our PostgreSQL tutorial series! In this video, we dive into the concept of constraints in PostgreSQL, focusing specifically on the UNIQUE key constraint. Understanding constraints is vital for maintaining data integrity and ensuring that your database follows your intended rules and structure.
We will walk you through what the UNIQUE key constraint is and why it's crucial in database management. You'll learn how this constraint prevents duplicate values in specified columns, enhancing data consistency and reliability. We’ll also demonstrate how to create and use the UNIQUE key constraint effectively in your PostgreSQL tables, including practical examples to solidify your understanding.
Whether you’re a beginner getting familiar with database concepts or an experienced developer refining your skills, this tutorial will provide you with the knowledge and confidence to implement UNIQUE key constraints efficiently. Stay tuned and level up your PostgreSQL expertise!
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Setting default values in PostgreSQL columns can streamline database management, improve consistency, and reduce the need for repetitive data entry. In this tutorial, you’ll learn how to define default values in PostgreSQL tables, making it easier to manage data across applications.
We'll dive into the syntax and usage of the DEFAULT keyword, demonstrating different use cases such as numeric defaults, text, and date values. This tutorial covers why defaults are essential for certain columns and shows how to make them work to your advantage, ensuring cleaner, more predictable data inputs.
Whether you’re a developer working on complex applications or a database administrator looking to automate routine tasks, understanding PostgreSQL’s default values can significantly simplify your workflow. Watch this video to gain practical insights and optimize your PostgreSQL tables for a more efficient database experience!
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In this video, we guide you through the process of connecting to a PostgreSQL Server using three widely used tools: pgAdmin, psql, and DBeaver. Whether you’re a beginner or an experienced user, understanding how to establish a connection to your PostgreSQL database is crucial for managing and querying data effectively.
First, we show you how to connect using pgAdmin, a popular graphical user interface tool that simplifies server management and database administration. Next, we demonstrate connecting via the psql command-line tool for those who prefer to work directly with SQL commands. Finally, we explore DBeaver, a universal database management tool that offers seamless PostgreSQL integration along with support for other databases.
By the end of this tutorial, you’ll have a solid understanding of how to use these tools to manage and interact with your PostgreSQL server. Make sure to watch, like, and subscribe for more comprehensive PostgreSQL tutorials!
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In this comprehensive tutorial, you'll learn how to create a database in PostgreSQL 16 using both pgAdmin 4 and the psql SQL Shell. Whether you're new to PostgreSQL or looking to expand your database management skills, this video provides step-by-step guidance on two popular methods for database creation. We'll start by walking you through the graphical interface of pgAdmin 4, ideal for beginners who prefer a user-friendly approach. Next, we'll dive into the command line with psql, where you'll learn the necessary SQL commands to create and manage databases efficiently. By the end of this video, you'll be equipped with the knowledge to set up your PostgreSQL environment and create databases using the method that best suits your workflow. Perfect for developers, database administrators, and anyone interested in mastering PostgreSQL 16.
Create table TestDemo(id numeric, name character varying(50) not null);
select version();
CREATE DATABASE testdemo2_db
WITH
OWNER = postgres
ENCODING = 'UTF8'
LC_COLLATE = 'English_United States.1252'
LC_CTYPE = 'English_United States.1252'
LOCALE_PROVIDER = 'libc'
TABLESPACE = pg_default
CONNECTION LIMIT = -1
IS_TEMPLATE = False;
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