How EXCEPT works in SQL? Best EXCEPT examples

How EXCEPT works in SQL? Best EXCEPT examples

When writing SQL queries, sometimes we need to compare two datasets and return the differences. One of the most effective ways to do this is by using the EXCEPT operator. If you’ve never used EXCEPT before, or if you’re unsure exactly how it works, this article will explain everything in detail.

What Is the EXCEPT Operator in SQL?

The EXCEPT operator in SQL retrieves unique rows from the first query that do not exist in the second query. It’s a powerful tool for identifying discrepancies between two datasets. Think of it as a “difference finder” between two result sets.

Here’s a quick breakdown of what EXCEPT does:

  • Compares two SELECT queries.
  • Returns only the rows that exist in the first query but not in the second.
  • Eliminates duplicate rows automatically.

Basic Syntax of EXCEPT

The syntax for using EXCEPT is straightforward:


SELECT column1, column2, ...
FROM table1
EXCEPT
SELECT column1, column2, ...
FROM table2;

Both SELECT statements involved must have the same number of columns, and these columns must have compatible data types.

Practical Examples of Using EXCEPT

1. Finding Records in One Table but Not in Another

Imagine we have two tables: Customers_2023 and Customers_2024. We want to get all customers from 2023 who are not present in 2024.


SELECT customer_id, name 
FROM Customers_2023
EXCEPT
SELECT customer_id, name 
FROM Customers_2024;

This returns all customers who were present in 2023 but did not continue in 2024.

2. Identifying Employees Who Have Left the Company

Suppose we have an Employees_2023 table and an Employees_2024 table, and we want to identify employees who left the company.


SELECT employee_id, name 
FROM Employees_2023
EXCEPT
SELECT employee_id, name 
FROM Employees_2024;

Any employee from 2023 who does not appear in 2024 will be listed.

Important Rules for Using EXCEPT

To ensure EXCEPT works correctly, keep these guidelines in mind:

  1. The number of columns in both queries must be the same.
  2. Data types of corresponding columns must be compatible.
  3. EXCEPT removes duplicates from the final output.

EXCEPT vs. NOT EXISTS vs. LEFT JOIN

While EXCEPT is useful, it’s not the only way to filter out differences. Here’s a comparison:

Method Description Performance Considerations
EXCEPT Finds rows in the first query that do not exist in the second. Automatically removes duplicates, may not be optimal for large datasets.
NOT EXISTS Checks if a subquery does not return any rows. Can be more efficient when proper indexes are used.
LEFT JOIN (WHERE NULL) Uses a left join and filters out matching rows. Can be optimized using indexing but may perform worse than EXCEPT in some cases.

Performance Considerations

While EXCEPT is simple to use, it may not always be the most efficient choice. Here are a few tips to improve performance:

  • Ensure both tables have indexes on the columns being compared.
  • Avoid unnecessary large dataset comparisons.
  • Consider using NOT EXISTS or LEFT JOIN for better performance with specific queries.

When Should You Use EXCEPT?

The EXCEPT operator is ideal in cases where:

  • You need to find records missing from one dataset.
  • You are working with structured datasets where duplicate removal is necessary.
  • The alternative methods, like LEFT JOIN, would be too complex for the intended query.

Final Thoughts

The EXCEPT operator is a highly useful SQL tool for comparing datasets and finding differences. Whether you’re tracking customer churn, identifying missing records, or ensuring data consistency, it can save you a lot of time and effort.

Next time you need to compare two tables, give EXCEPT a try. Just remember its rules and limitations, and you’ll be able to use it effectively in your queries.

 

Other interesting article:

How INTERSECT works in SQL? Best INTERSECT examples