In this video (#54 of our PostgreSQL Full Playlist), we dive deep into the XML Data Type in PostgreSQL — a powerful and structured way to store and process XML content directly in your database!
We start by exploring how the xml type differs from regular text, including its built-in validation for well-formed XML and compatibility with XML functions like xmlparse, xmlserialize, and xpath.
You’ll learn:
How to insert XML documents and fragments using XMLPARSE
PostgreSQL-specific shorthand syntax for XML data
How to convert XML back into text format using XMLSERIALIZE
Encoding best practices to avoid client-server issues
How to query XML using xpath() for data extraction
Workarounds for indexing XML using full-text search
Checking whether a stored XML value is a document or content fragment
This video also covers best practices, potential pitfalls, and performance tuning advice when working with XML data in PostgreSQL.
Whether you're building APIs, handling metadata, or managing config files — XML in PostgreSQL is a must-have tool in your toolkit. Don't forget to watch till the end and subscribe for more database tutorials!
📌 Subscribe for the full PostgreSQL series and stay updated with all episodes.
🧠 Chapters are included for quick navigation.
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!
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!
Welcome to Part 45 of our PostgreSQL Full Course Playlist! 🚀
In this video, we dive deep into one of the most fundamental aspects of PostgreSQL — Character Data Types. You'll learn the key differences, use cases, and behaviors of:
CHAR(n) – fixed-length, space-padded strings
VARCHAR(n) – variable-length strings with a defined limit
TEXT – flexible and unbounded character storage
Internal types like bpchar, "char", and name
🎯 We'll cover real-world examples like storing employee codes, customer names, blog content, product SKUs, and user feedback. You'll also learn the implications of trailing spaces, padding, truncation, and storage behavior.
💡 This session is crucial for anyone designing tables, optimizing storage, or simply trying to choose the best string type in PostgreSQL.
Whether you're a student, backend developer, or DBA — by the end of this video, you'll know when to use TEXT over VARCHAR, why CHAR can be risky, and how PostgreSQL handles string storage under the hood.
📌 Topics Covered:
Syntax & behavior of CHAR, VARCHAR, and TEXT
Storage internals (TOAST, compression, padding)
Behavior with trailing spaces
Comparison semantics and limitations
Best practices for choosing the right type
👉 Don't forget to like, comment, and subscribe for more deep-dive videos in this PostgreSQL series.
📽️ Next Video: Data Types In PostgreSQL – Binary Data Types
In this video (PostgreSQL Playlist #44), we take a deep dive into the money data type in PostgreSQL, which is specially designed to store and manipulate currency values with fixed fractional precision.
💡 You’ll learn:
What the money type is and how it works
How to create tables and insert monetary values
Type casting between money, numeric, and float
Performing arithmetic with money values
Real-world example: applying discounts on invoices
Best practices to avoid rounding errors and locale mismatches
🛠️ This tutorial is perfect for developers, data engineers, and students looking to enhance their PostgreSQL database design and financial data handling skills.
📌 Don’t forget to check out the complete PostgreSQL series for more in-depth tutorials.
Subscribe for more database and backend content, and hit the 🔔 to stay updated!
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.
Welcome to Best PostgreSQL Tutorial Video #30!
In this tutorial, we explore DELETE Data Options in PostgreSQL, an essential part of Data Manipulation Language (DML). You will learn how to delete specific rows, multiple rows based on conditions, and all rows from a table safely and efficiently.
We cover:
✅ Basic DELETE syntax to remove rows using conditions.
✅ How to delete data using the primary key for targeting specific rows.
✅ How to delete multiple rows with flexible WHERE conditions.
✅ RETURNING clause to view deleted rows immediately.
✅ Advanced DELETE using USING clause for join-based deletions.
✅ Difference between DELETE and TRUNCATE commands.
✅ Best practices and caution points while using DELETE to avoid accidental data loss.
💡 Whether you're a beginner or an experienced PostgreSQL user, this tutorial will clarify all use cases of the DELETE command with practical examples, tips, and recommendations.
📊 Check out practical examples like deleting based on price, stock, and product names, and learn how to handle deletion efficiently in real-world databases.
👉 Don't forget to Like, Share, and Subscribe for more PostgreSQL tutorials and database management insights!
The UPDATE statement in PostgreSQL is a crucial tool for modifying existing records within a table. Whether you need to update specific rows, apply conditional changes, or modify multiple columns at once, PostgreSQL provides powerful options to handle data updates efficiently.
In this tutorial, we explore various UPDATE scenarios:
✅ Basic updates for modifying specific rows
✅ Applying updates to all rows with calculations
✅ Updating multiple columns in a single query
✅ Using conditions with AND/OR operators
✅ Updating data based on subqueries
✅ Returning updated rows with the RETURNING clause
✅ Safe updates using primary keys
✅ Updating data through JOINs with other tables
✅ Applying conditional updates using CASE
✅ Using Common Table Expressions (CTEs) for structured updates
We also cover essential best practices to ensure safe updates, avoid unwanted modifications, and optimize query performance.
📌 SQL Examples Covered in the Video:
UPDATE products SET price =200WHERE price =300;
UPDATE products SET price = price *1.10;
UPDATE products SET price = price *1.05, stock = stock -2WHERE stock >5;
UPDATE products SET stock = stock +5WHERE name ='Laptop'OR price <200;
UPDATE products SET price = price *1.10WHERE product_id IN (SELECT product_id FROM products WHERE stock <15);
... and many more!
🚀 By the end of this tutorial, you’ll have a solid understanding of how to effectively use the UPDATE statement in PostgreSQL for data manipulation.
🔔 Don't forget to like, share, and subscribe for more PostgreSQL tutorials!
🚀 Mastering INSERT Data Options in PostgreSQL! 🛠️
When working with PostgreSQL, inserting data efficiently can make a big difference in performance. In this tutorial, we cover everything about the INSERT statement—from basic syntax to advanced techniques like batch inserts, conflict resolution (ON CONFLICT), bulk loading with COPY, and even inserting JSON data.
📌 What You’ll Learn in This Video: ✅ Basic INSERT statement and its syntax
✅ Using DEFAULT values when inserting rows
✅ Bulk Inserts with multi-row VALUES
✅ Efficient data insertion using COPY for large datasets
✅ ON CONFLICT (UPSERT) to handle duplicate key conflicts
✅ Using RETURNING to fetch inserted data
✅ Dynamic batch inserts with UNNEST function
✅ Storing and inserting JSON data in PostgreSQL
✅ Performance tips for efficient data manipulation
🔥 Code Examples Covered: 🔹 Creating a sample table and inserting data
🔹 Inserting data with and without specifying column names
🔹 Handling default values while inserting rows
🔹 Using INSERT ... SELECT to copy data from another table
🔹 Performing bulk inserts for large datasets
🔹 Leveraging ON CONFLICT for safe upserts
🔹 Batch inserts using PostgreSQL’s UNNEST function
🔹 Inserting JSON data into PostgreSQL
💡 Performance Optimization Tips:
🚀 Use COPY instead of multiple INSERT statements for large datasets
🚀 Batch inserts with multi-row VALUES improve efficiency
🚀 Temporarily disable indexes for massive data inserts
🚀 Optimize conflict resolution using ON CONFLICT
🎯 Whether you're a beginner or an experienced developer, this video will help you optimize your PostgreSQL inserts and improve database performance!
🔔 Subscribe for More PostgreSQL Tutorials! Don't forget to like, share, and comment with your thoughts! 😊
#PostgreSQL#Database#SQL#DataManipulation#SQLPerformance#DBMS
Are you looking to access external data in PostgreSQL without duplicating it? PostgreSQL's Foreign Data Wrappers (FDW) allow you to integrate data from remote databases seamlessly! 🚀
In this tutorial, we will walk you through creating a PostgreSQL Foreign Table step by step. You'll learn how to use FDWs to connect to external databases, query foreign data as if it were local, and even perform modifications based on FDW capabilities.
🔹 Topics Covered:
✅ What is Foreign Data in PostgreSQL?
✅ Understanding Foreign Data Wrappers (FDW)
✅ Creating a Foreign Data Wrapper
✅ Defining a Foreign Server and User Mapping
✅ Creating and Querying a Foreign Table
✅ Modifying and Importing Foreign Data
💡 Why Use Foreign Tables?
Combine data from multiple databases without duplication
Improve reporting and analytics by accessing external sources
Enhance microservices and distributed system interactions
By the end of this video, you’ll have a fully functional foreign table setup in PostgreSQL, allowing you to efficiently query and manage remote data!
📌 Don't forget to LIKE 👍, SHARE, and SUBSCRIBE 🔔 for more in-depth PostgreSQL tutorials!
#PostgreSQL#ForeignTable#FDW#DatabaseIntegration#SQL#PostgreSQLTutorial
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!
🔔 Subscribe now for more PostgreSQL tutorials! 📢 Like, Share & Comment your thoughts!
Row-Level Security (RLS) in PostgreSQL is a powerful feature that provides fine-grained access control by restricting data access at the row level. With RLS, you can enforce policies to ensure users interact only with the data they are authorized to view or modify.
🔑 Key Features of RLS:
Flexible Policies: Define access rules based on user-specific conditions.
Table-Specific Security: Apply RLS selectively to individual tables.
Transparent Enforcement: Policies are enforced automatically for restricted users.
In this video, you'll learn:
1️⃣ How to enable RLS for a PostgreSQL table.
2️⃣ The steps to define and apply policies for SELECT, INSERT, UPDATE, and DELETE operations.
3️⃣ Practical examples of securing data with RLS policies.
4️⃣ Testing and verifying policy enforcement for restricted users.
👩💻 Real-World Examples:
We'll demonstrate how RLS can restrict access to the hr_schema.employees table, ensuring users only interact with their own data while superusers maintain broader privileges.
📚 Why RLS Matters:
RLS helps secure sensitive data, enforce compliance, and simplify multi-user data management, making PostgreSQL an excellent choice for high-security applications.
Stay tuned until the end for tips on managing and removing policies when needed. Start implementing RLS today and take your PostgreSQL skills to the next level!
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Access Control Lists (ACLs) are at the core of database security in PostgreSQL. They determine who can perform specific actions on database objects like tables, sequences, and more. This tutorial breaks down PostgreSQL privileges, their representations, and practical examples to help you understand and implement them effectively.
Learn how privileges are granted, revoked, and managed. Explore commands like GRANT and REVOKE to define access permissions, and dive into ACL abbreviations to interpret privilege details. You'll also see how to check access privileges using the \dp command.
Key Highlights:
Granting privileges with options for SELECT, INSERT, UPDATE, DELETE, and more.
Viewing access privileges for database objects.
Understanding ACL entries and their abbreviations.
Practical examples for real-world scenarios.
Whether you're managing a small database or a large enterprise system, mastering ACLs will enhance your database security and control. Watch this video to elevate your PostgreSQL skills!
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Transform your PostgreSQL tables like a pro! This video dives deep into the versatile ALTER TABLE command, showing you how to efficiently modify table structures and enhance your database schema. Whether you're adding new columns, updating constraints, or even renaming tables, we've got you covered with practical examples and best practices.
🔍 Topics Covered:
Adding columns with default values or constraints.
Removing unwanted columns from tables.
Adding powerful constraints like CHECK, UNIQUE, PRIMARY KEY, and FOREIGN KEY.
Dropping constraints when no longer needed.
Changing default values and data types of columns.
Renaming columns and even entire tables.
📚 Hands-on Examples:
1️⃣ Create a products table with essential fields.
2️⃣ Add constraints to ensure data integrity.
3️⃣ Explore how to rename columns and tables for better clarity.
4️⃣ Learn techniques to safely drop constraints and update schemas.
By the end of this tutorial, you'll have the knowledge to adapt your PostgreSQL tables to meet evolving business requirements with confidence. Whether you're a beginner or an experienced database administrator, this guide will sharpen your skills.
👉 Don't forget to like, subscribe, and hit the bell icon to stay updated with the best PostgreSQL tutorials!
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Discover the hidden power of System Columns in PostgreSQL tables! These special columns, automatically created for every table, store essential metadata about the table and its rows. Reserved for internal use, their names can't be repurposed for user-defined columns.
🔍 What's inside this video?
tableoid: Identify the table each row belongs to, especially in partitioned or inherited tables.
xmin and xmax: Transaction IDs for inserted and deleted rows, providing insight into row history.
cmin and cmax: Command identifiers for insertions and deletions, offering detailed transaction tracking.
ctid: Pinpoint the physical location of row versions within a table, with tips on why it shouldn't be used as a long-term identifier.
With hands-on examples, you'll see how these columns can assist in debugging, understanding table inheritance, and managing complex database systems. Whether you're a PostgreSQL enthusiast or a seasoned DBA, this video unlocks advanced capabilities for managing row states and transaction details.
🛠️ Master these system columns to level up your PostgreSQL expertise!
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In this video, we explore the essential concept of Primary Key constraints in PostgreSQL. Understanding Primary Keys is fundamental for designing robust and efficient database tables, ensuring data integrity and consistency.
A Primary Key constraint guarantees that a column, or a group of columns, can be used as a unique identifier for rows in a table. It requires that values in these columns be both unique and not null. We will walk through practical examples to clarify these concepts:
Example 1: Using individual UNIQUE and NOT NULL constraints to enforce data uniqueness and prevent null entries.
Example 2: Simplifying table design with a PRIMARY KEY constraint, which automatically enforces both uniqueness and non-null properties.
Example 3: Naming a PRIMARY KEY constraint and understanding its importance in database documentation.
Example 4: Defining a PRIMARY KEY that spans multiple columns, which is useful in more complex scenarios.
By the end of this video, you'll grasp how Primary Key constraints work, why they are vital, and best practices for their usage. We’ll also cover automatic index creation by PostgreSQL when a Primary Key is defined and discuss table constraint rules, including the significance of having only one Primary Key per table.
This tutorial is a must-watch if you are aiming to design efficient, reliable, and well-structured databases in PostgreSQL. Stay tuned for our next lesson on Foreign Keys to build on this foundational knowledge!
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!
#PostgreSQL#pgAdmin#psql#DBeaver#PostgreSQLTutorial#DatabaseManagement#SQL#TechTutorial#DBMS#DataEngineering#OpenSourceDatabase#PostgreSQLServer#DatabaseTools#DatabaseConnection#PostgreSQLShorts
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Welcome to our comprehensive tutorial on downloading and installing PostgreSQL 17 and pgAdmin 4 on Windows! In this video, we will walk you through every step of the installation process, ensuring you have a smooth setup. PostgreSQL is a powerful, open-source relational database management system, and pgAdmin 4 is a robust management tool that allows you to interact with your PostgreSQL databases effortlessly.
First, we’ll cover the prerequisites you need before starting the installation. We'll show you how to download PostgreSQL 17 from the official website, ensuring you get the latest version. Next, we will guide you through the installation process, including choosing the right options for your setup and configuring your database environment.
Once PostgreSQL is installed, we’ll dive into installing pgAdmin 4, an essential tool for managing your databases with a user-friendly interface. You’ll learn how to set up your first database, navigate the pgAdmin interface, and execute basic SQL commands.
By the end of this tutorial, you will have a fully functional PostgreSQL environment ready for your development projects. Whether you're working on a personal project or need a powerful database solution for your business, this video has you covered.
Make sure to subscribe to our channel for more tutorials on database management and development tips! If you have any questions or run into issues, feel free to drop a comment below—we’re here to help!
In this video, I will guide you through the process of changing column data types in PostgreSQL without losing any data. This tutorial is essential for anyone looking to update their database schema safely and efficiently, ensuring data integrity is maintained throughout the process.
In this tutorial, you’ll learn:
• Introduction to Data Type Changes: Understand the importance and common scenarios for changing column data types in PostgreSQL.
• Preparing for Data Type Changes: Learn how to prepare your database and data for changing column data types, including creating backups and understanding the implications of the change.
• Changing Column Data Types Safely: Step-by-step instructions on how to change column data types in PostgreSQL without losing data, including necessary SQL commands and best practices.
• Handling Common Data Type Conversions: Explore how to handle common data type conversions, such as converting between text, integer, and date types, with examples.
• Troubleshooting Data Type Change Issues: Tips for troubleshooting common issues that may arise during the data type change process, ensuring your database remains functional and data remains intact.
• Best Practices for Schema Changes: Gain insights into best practices for making schema changes, including minimizing downtime, validating changes, and testing thoroughly.
Whether you’re a database administrator, developer, or anyone responsible for managing PostgreSQL databases, this video provides valuable insights and practical advice to help you change column data types effectively and safely.
🎥 Watch the full video [here]
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Source Codes:
-- How To Change Column Data Types in PostgreSQL Without Losing Data
-- Case 1: Simple Data Type Change (e.g., INTEGER to BIGINT)
ALTER TABLE table_name
ALTER COLUMN column_name TYPE BIGINT;
-- Create the sample table with an INTEGER column
CREATE TABLE sample_table_int (
id SERIAL PRIMARY KEY,
some_integer INTEGER
);
-- Insert sample data into the table
INSERT INTO sample_table_int (some_integer) VALUES
(100),
(200),
(300);
select * from sample_table_int;
-- Change the column type from INTEGER to BIGINT
ALTER TABLE sample_table_int
ALTER COLUMN some_integer TYPE BIGINT;
-- Verify the changes
SELECT * FROM sample_table_int;
-- Case 2: Data Type Change with Using Clause (e.g., VARCHAR to INTEGER)
ALTER TABLE table_name
ALTER COLUMN column_name TYPE INTEGER USING column_name::INTEGER;
-- Create the sample table with a VARCHAR column
CREATE TABLE sample_table_varchar_to_int (
id SERIAL PRIMARY KEY,
some_varchar VARCHAR(10)
);
-- Insert sample data into the table
INSERT INTO sample_table_varchar_to_int (some_varchar) VALUES
('100'),
('200'),
('300');
-- Change the column type from VARCHAR to INTEGER using the USING clause
ALTER TABLE sample_table_varchar_to_int
ALTER COLUMN some_varchar TYPE INTEGER USING some_varchar::INTEGER;
-- Verify the changes
SELECT * FROM sample_table_varchar_to_int;
-- Case 3: Data Type Change with Complex Transformation
--Add a New Temporary Column:
ALTER TABLE table_name ADD COLUMN new_column_name NEW_DATA_TYPE;
--Update the New Column with Transformed Data:
UPDATE table_name SET new_column_name = transformation_function(old_column_name);
--Drop the Old Column:
ALTER TABLE table_name DROP COLUMN old_column_name;
--Rename the New Column:
ALTER TABLE table_name RENAME COLUMN new_column_name TO old_column_name;
--Example: Changing VARCHAR to DATE
-- Create the sample table with a VARCHAR column
CREATE TABLE sample_table (
id SERIAL PRIMARY KEY,
old_varchar_date VARCHAR(10)
);
-- Insert sample data into the table
INSERT INTO sample_table (old_varchar_date) VALUES
('2023-01-01'),
('2023-02-15'),
('2023-03-20');
select * from sample_table;
-- Add a new temporary column with the desired data type
ALTER TABLE sample_table ADD COLUMN new_date_column DATE;
-- Update the new column with transformed data from the old column
UPDATE sample_table SET new_date_column = to_date(old_varchar_date, 'YYYY-MM-DD');
-- Drop the old column
ALTER TABLE sample_table DROP COLUMN old_varchar_date;
-- Rename the new column to the old column’s name
ALTER TABLE sample_table RENAME COLUMN new_date_column TO old_varchar_date;
-- Verify the changes
SELECT * FROM sample_table;
--Remember to build indexes on new column if there was index existing to get optimized performance
