Difference Between DDL and DML in DBMS

In the realm of Database Management Systems (DBMS), SQL (Structured Query Language) is divided into various types of commands, each serving a specific purpose. Two primary types of SQL commands are Data Definition Language (DDL) and Data Manipulation Language (DML). Understanding the differences between DDL and DML is crucial for anyone working with databases, as these commands perform fundamentally different functions. 

Overview of DDL and DML

Data Definition Language (DDL)

DDL commands are used to define and modify the structure of database objects such as tables, indexes, and views. They are primarily concerned with the schema of the database.

Data Manipulation Language (DML)

DML commands are used to manipulate data stored in the database. They are focused on inserting, updating, deleting, and retrieving data from the database tables.

Key Differences Between DDL and DML

Purpose

  • DDL: DDL commands define, alter, and manage the structure of database objects. They do not handle the data within these objects but rather the objects themselves.
  • DML: DML commands are used to manipulate the data within the database objects. They handle data operations like insertions, updates, deletions, and data retrieval.

Commands

  • DDL Commands: CREATE, ALTER, DROP, TRUNCATE
  • DML Commands: INSERT, UPDATE, DELETE, SELECT

Execution

  • DDL: DDL commands are auto-committed, meaning that once executed, the changes are immediately saved in the database. They cannot be rolled back.
  • DML: DML commands are not auto-committed. They require an explicit COMMIT to save the changes permanently. They can be rolled back before the COMMIT is executed.

Transaction Control

  • DDL: DDL commands do not support transaction control. Once executed, the changes are permanent.
  • DML: DML commands support transaction control. They allow for ROLLBACK to undo changes before committing them.

Effect

  • DDL: DDL commands affect the entire schema or database objects.
  • DML: DML commands affect the data within the database objects.
  • Impact
  • DDL: DDL operations can potentially impact the database structure significantly, such as dropping a table which removes all its data and structure.
  • DML: DML operations impact only the data within the database objects, not the structure of the objects themselves.

Difference Between DDL and DML

Data Definition Language (DDL) and Data Manipulation Language (DML) are two categories of SQL (Structured Query Language) statements used to manage databases. They serve distinct purposes in defining and manipulating data structures and content. Here’s a comparison of their main differences:

Feature DDL DML
Full Form Data Definition Language Data Manipulation Language
Purpose Define and manage structure of database objects Manipulate data within database objects
Operations Create, alter, and drop objects (e.g., tables) Select, insert, update, delete data
Examples CREATE TABLE, ALTER TABLE, DROP TABLE SELECT, INSERT, UPDATE, DELETE
Effect on Data Changes database schema Changes data content
Transaction Scope Typically autocommitted May require explicit transaction management
Granularity Operates at the level of entire database objects Operates at the level of individual data records
Concurrency Can impact concurrent transactions (locks) Can be concurrent with other DML operations
Transaction Safety Generally safe within transactions Requires careful management within transactions
Typical Use Cases Setting up database schema, data definition Application-level data manipulation

Conclusion

Understanding the differences between DDL and DML commands in SQL is crucial for effective database management. DDL commands are used to define and modify the structure of database objects, impacting the schema and structure of the database. In contrast, DML commands are used to manipulate the data within these objects, focusing on inserting, updating, deleting, and retrieving data.

By mastering both DDL and DML commands, you can efficiently create, modify, and manage the structure of your databases while also handling the data stored within them. This knowledge is fundamental for database administrators, developers, and anyone working with database systems.

Difference Between DDL and DML in DBMS

Published on 02-Jul-2024 9:13:20

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