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How to Delete Column in SQL

How to Delete Column in SQL

If you’re working with a database in SQL, there may come a time when you need to delete a column from a table. Whether you’re restructuring your database, cleaning up unused columns, or simply adjusting your data model, deleting a column can be a useful tool.

However, if you’re new to SQL, you may be unsure of how to go about deleting a column correctly. In this blog post, we’ll explain the process of deleting a column from a SQL table step-by-step, and provide examples to help you understand the process. By the end of this post, you’ll be able to confidently remove columns from your SQL tables without causing any damage to your database.

Importance of Being Careful While Deleting Columns:

Before you delete a column in SQL, it is important to understand why this action should be done cautiously. Deleting an entire table or column can cause data loss or break existing applications or code. Therefore, it’s important to delete columns only when there is no other option and you have a good understanding of the implications. You should also make sure to take a backup of the data and code before deleting any columns in SQL.

Deleting Column in SQL- A Step-By-Step Guide:

Step 1: Checking Table Structure

Retrieving Table Structure using SQL Command:

Before deleting any column, it is important to know the structure of the table and the data contained in it. You can check if a particular column exists or not by executing an SQL statement like “DESCRIBE tablename;” or “SELECT * FROM tablename;”. This will provide you with detailed information about the table structure, including column names and data types.

Reviewing Columns to Identify the Column to be Deleted:

Once you have retrieved the table structure, you can review the columns and identify which column to delete. You should consider factors like data type and whether the column is referenced in any other tables or views before deleting it. You should also consider the implications of deleting a column, such as data loss or breaking existing applications.

Step 2: Backing up the Data

Backing up the Table Data to Avoid Accidental Data Loss:

Before deleting a column, it is important to back up the existing table data. This will help you avoid any accidental data loss due to incorrect syntax or unexpected behavior. You can create a backup of the table data by executing an SQL statement like “SELECT * FROM tablename INTO OUTFILE ‘backup_file.csv’”. This will create a CSV file with the entire data from the table and can be used for restoring the data later.

Creating a Temporary Table to Store the Data:

If you don’t want to create a CSV file, then you can also create a temporary table to store the existing data. This is done by executing an SQL statement like “CREATE TEMPORARY TABLE temp_tablename AS SELECT * FROM tablename;”. This will create a temporary table with the existing data from the original table and can be used for restoring the data later.

Step 3: Alter Table Statement

Using the ALTER TABLE Statement to Delete a Column:

Once you have backed up the data, you can proceed with deleting the column. This is done by executing an ALTER TABLE statement with a DROP COLUMN clause like “ALTER TABLE tablename DROP COLUMN colname;”. This will delete the specified column from the table.

Syntax and Example of the ALTER TABLE Statement:

The exact syntax of the ALTER TABLE statement varies depending on the database system you are using. You can refer to the database documentation for exact syntax and examples. Some commonly used databases like MySQL, Oracle, and Microsoft SQL Server provide simple syntax like “ALTER TABLE tablename DROP COLUMN colname;”.

Step 4: Updating Referencing Objects

Identifying Objects that Reference the Deleted Column:

If the deleted column is referenced in any other tables or views, then those objects need to be updated as well. You can identify these referencing objects by executing a query like “SELECT * FROM information_schema.columns WHERE table_name = ‘tablename’ AND column_name = ‘colname’;”. This will list all the referencing objects and their details.

Updating Referencing Objects to Avoid Errors:

Once you have identified the referencing objects, you can update them to avoid any errors. Depending on the type of referencing object, you may need to drop and recreate it or alter the existing object. For example, if a view is referencing the deleted column, then you may need to drop and recreate it with the updated columns list.

Modifying or Deleting the Referencing Objects as Needed:

After updating the referencing objects, you may need to modify or delete them as needed. For example, if a view is no longer required due to the deletion of the column, then you can drop it by executing an SQL statement like “DROP VIEW view name;”. This will delete the referencing object and help you avoid any errors.

Step 5: Recreating the Table

Recreating the Table and Restoring the Data:

Once you have modified or deleted any referencing objects, you can recreate the table with the updated columns list. You will also need to restore the data from either the backup CSV file or the temporary table created earlier. This can be done by executing an SQL statement like “INSERT INTO tablename SELECT * FROM temp_tablename;”. This will recreate the table with updated columns and also restore the data from the temporary table.


Deleting a column from a SQL table is a straightforward process that can be accomplished in a few simple steps. By using the ALTER TABLE statement and specifying the column you want to remove, you can easily delete unwanted columns from your SQL tables. However, it’s important to remember that deleting a column will permanently remove all the data contained within it, so be sure to make a backup of your data before making any changes. With this knowledge, you can now confidently manage your SQL tables and keep your database organized and efficient. As with any aspect of SQL, the more you practice and familiarize yourself with the syntax and commands, the easier it will become to work with SQL and achieve your goals.


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