IS NULL vs equals NULL in SQL - Performance Comparison

Time Complexity: IS NULL vs equals NULL

O(n)

Understanding Time Complexity

We want to understand how checking for NULL values in SQL affects the time it takes to run a query.

Specifically, we ask: Does using IS NULL or = NULL change how long the query takes as data grows?

Scenario Under Consideration

Analyze the time complexity of these two queries:

-- Using IS NULL
SELECT * FROM employees WHERE manager_id IS NULL;

-- Using equals NULL
SELECT * FROM employees WHERE manager_id = NULL;
    

Both queries try to find rows where manager_id is missing, but use different syntax.

Identify Repeating Operations

Look at what repeats as the database checks each row:

• Primary operation: Checking the manager_id value for each row.
• How many times: Once per row in the employees table.

How Execution Grows With Input

As the number of rows grows, the database must check more values:

Input Size (n)	Approx. Operations
10	10 checks
100	100 checks
1000	1000 checks

Pattern observation: The number of checks grows directly with the number of rows.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the query grows in a straight line as the table gets bigger.

Common Mistake

[X] Wrong: "Using = NULL works the same as IS NULL and returns the right rows."

[OK] Correct: In SQL, = NULL never matches any row because NULL means unknown, so this condition always fails. Only IS NULL correctly finds rows with missing values.

Interview Connect

Understanding how NULL checks work and their cost helps you write correct and efficient queries, a skill valued in real projects and interviews.

Self-Check

"What if we add an index on manager_id? How would that change the time complexity of the IS NULL query?"