Comparison of TRUNCATE, DELETE, and DROP in SQL

Here’s a comparison of TRUNCATE, DELETE, and DROP in SQL, highlighting their differences and use cases:

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1. TRUNCATE

• Purpose: Removes all rows from a table quickly without logging individual row deletions.
• Key Points:
  • DDL (Data Definition Language) operation.
  • Does not log individual row deletions (minimally logged).
  • Cannot use a WHERE clause (it clears the entire table).
  • Resets any identity/autoincrement columns.
  • Cannot be rolled back in some databases (e.g., MySQL without transaction support).
  • Preserves the table structure, indexes, and constraints.

Example:

TRUNCATE TABLE my_table;

Use Case: When you need to quickly clear all data from a table but retain the structure.

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2. DELETE

• Purpose: Removes rows from a table based on a condition.
• Key Points:
  • DML (Data Manipulation Language) operation.
  • Logs each row deletion (fully logged).
  • Supports a WHERE clause to selectively delete rows.
  • Can be rolled back if inside a transaction.
  • Does not reset identity/autoincrement columns.

Example:

DELETE FROM my_table WHERE column_name = 'value';

Use Case: When you need to remove specific rows or perform deletions in a transactional context.

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3. DROP

• Purpose: Completely removes a table (or other database objects) from the database.
• Key Points:
  • DDL (Data Definition Language) operation.
  • Deletes the table structure, data, indexes, constraints, and any dependent objects.
  • Cannot be rolled back.
  • Requires recreating the table if needed again.

Example:

DROP TABLE my_table;

Use Case: When you no longer need the table or its data.

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Summary Table:

Feature	TRUNCATE	DELETE	DROP
Operation Type	DDL	DML	DDL
Removes Data?	Yes	Yes (conditionally)	Yes (completely)
Removes Table Structure?	No	No	Yes
Can Use WHERE Clause?	No	Yes	No
Rollback Possible?	No (depends on DB)	Yes	No
Resets Identity Columns?	Yes	No	N/A
Speed	Faster than DELETE	Slower (fully logged)	Fast