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DML and DDL in SQL – Explain SQL Commands in Detail

  • Written By The IoT Academy 

  • Published on February 14th, 2024

In the realm of database management, understanding the nuances of DML and DDL in SQL is paramount. These two sets of commands play a pivotal role in shaping and maintaining the structure and content of a database. However, In this comprehensive guide, we delve into the intricacies of DML and DDL, elucidating their significance, and differences, and providing practical examples to solidify your understanding.

Understanding Data Manipulation Language (DML)

DML comprises a set of SQL commands used for managing data within a database. These commands facilitate the retrieval, insertion, modification, and deletion of data from database tables. The primary focus of DML is on manipulating the records stored in the database.

What is SQL?

SQL, also known as Structured Query Language, is a common computer language for handling databases. However, It helps to get, add, change, or remove data from databases using commands called queries. As well as This lets people interact with databases easily.

These commands set up, change, or delete the way a database works and handle the data inside it. SQL is really important for managing data well in all sizes of businesses and is used in different kinds of database systems.

Types of DML Commands

DML commands are used to handle data in a database. However, The main types of DML commands in SQL (Structured Query Language) include:

  • SELECT: Used to retrieve data from one or more tables.
  • INSERT: Adds new records to a table.
  • UPDATE: Modifies existing records within a table.
  • DELETE: Removes records from a table.

Moreover, DML commands are essential for managing and changing data in databases like MySQL, PostgreSQL, SQL Server, Oracle, and others.

Examples of DML Commands

Let’s consider a practical example of each DML command:

  • SELECT: SELECT * FROM Employees WHERE Department = ‘Marketing’;
  • INSERT: INSERT INTO Employees (Name, Age, Department) VALUES (‘Ankit Roy’, 62, ‘SEO’);
  • UPDATE: UPDATE Employees SET Department = ‘HR’ WHERE Name = ‘Shriyansh Tiwari’;
  • DELETE: DELETE FROM Employees WHERE Age > 60;

What is Data Definition Language (DDL)?

Exploring Data Definition Language (DDL) means learning about commands to make, change, or remove things. Like tables, indexes, and views in a database. Unlike DML, which deals with data, DDL deals with how the database is set up. As well as Important DDL commands include CREATE (to make new things), ALTER (to change things), and DROP (to remove things). As well as DDL helps manage the structure of the database, keeping data organized and working well.

DDL Commands in SQL

DDL commands in SQL are used to create, change, or delete the design of a database. These commands include:

  • CREATE: Builds new database objects such as tables, indexes, or views.
  • ALTER: Modifies existing database objects, allowing changes to their structure.
  • DROP: Deletes database objects, removing them from the database entirely.

However, These commands are very important for organizing how a database works, making sure it fits the needs of the program, and keeping data safe.

DDL vs DML Key Differences

Here’s a comparison table outlining the key difference between Data Definition Language and Data Manipulation Language or DML and DDL in SQL:

Feature DDL (Data Definition Language) DML (Data Manipulation Language)

Purpose

Defines and manages the structure of database objects

Manipulates data within those defined structures

Effect on Data

Alters the structure or schema of the database.

Alters the content or rows within the database.

Transaction Control

Typically auto-committed.

Can be part of transactions and rolled back if necessary.

Dependency

Can affect DML operations.

Independent of DDL operations.

Execution

Generally executed less frequently.

Executed more frequently as part of routine operations.

Concurrent operations

Usually locks the entire table or object being modified, affecting concurrent DML operations.

Can be concurrent with other DML operations but may face contention due to locking.

Examples

CREATE TABLE, ALTER TABLE, DROP TABLE, CREATE INDEX, etc.

SELECT, INSERT, UPDATE, DELETE, MERGE, etc.

 

This table shows the difference between DML and DDl, How they affect data, when they’re used if they’re part of transactions, if they depend on each other, how often they’re run, and if they can be done at the same time. It also gives examples of each.

DDL and DML Examples

Consider the following examples of DDL and DML commands in action:

  • DDL Example: `CREATE TABLE Employees (ID INT, Name VARCHAR(50), Department VARCHAR(50));`
  • DML Example: `INSERT INTO Employees (Name, Age, Department) VALUES (‘Ankit Roy, 82, ‘SEO’);`

Our Learners Also Read: PostgreSQL Tutorial for Beginners – Best Way to Learn PostgreSQL

Conclusion

Learning DDL and DML commands in SQL is crucial for managing databases well. Understanding how these commands work helps you organize data and shape your database. Ultimately, This guide on DML and DDL in SQL, with simple examples and explanations, is helpful for beginners and experienced SQL users alike. Keep practicing and improving your SQL skills to make the most out of database management.

Frequently Asked Questions
Q. What are DML types?

Ans. DML types are different ways to change or work with data in a database. The main DML types are:
SELECT: Gets data from tables.
INSERT: Put new records into a table.
UPDATE: Changes existing records in a table.
DELETE: Takes out records from a table. These commands let users do different things with the data in the database.

Q. What is DML INSERT?

Ans. DML INSERT is a way to put new information into a table in a database. It lets you say what you want to add for each part of the table, making a new row of data. This helps to fill up tables with new information, making it easier to work with the database.

About The Author:

The IoT Academy as a reputed ed-tech training institute is imparting online / Offline training in emerging technologies such as Data Science, Machine Learning, IoT, Deep Learning, and more. We believe in making revolutionary attempt in changing the course of making online education accessible and dynamic.

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