# Why NULL never compares false to anything in SQL

One of the most common questions SQL beginners have is why NULL values “don’t work right” in WHERE clauses. In this article I’ll explain it in a way I hope will make sense and be easy to remember.

If you’re new to SQL and have a hard time understanding this article, I encourage you to keep puzzling over it until the light comes on. I had to do that myself (and I’ve had to think hard about it to write this article), and I’ve seen a number of people learn SQL. NULLs always seem to be an important sticking point.

### The query that won’t work right

Here are two common queries that just don’t work:

select * from table where column = null;

select * from table where column <> null;

They both return no rows! Countless SQL veterans have tried to explain this one to beginners. The beginner usually thinks the first row should return rows where c1 is NULL. The veteran then points out that NULL is never equal to anything. The beginner then thinks, “if NULL isn’t equal to anything, then ‘WHERE COLUMN IS NOT EQUAL TO NULL’ is always true, so the second query should return all results!” The second WHERE clause is the logical opposite of the first, right? Right? Sadly, no it’s not.

### The real problem: a language trap

The beginner has fallen into a language trap, which the experienced programmer probably set by saying “NULL is never equal to anything.” That statement seems to imply “NULL is NOT EQUAL TO.” Unfortunately, that’s wrong. Not only is NULL not equal to anything, it’s also not unequal to anything. This is where the language is confusing.

The truth is, saying anything with the words “equal” or “not equal” is a trap when discussing NULLs, because there is no concept of equality or inequality, greater than or less than with NULLs. Instead, one can only say “is” or “is not” (without the word “equal”) when discussing NULLs.

### The right way to think about NULL

The correct way to understand NULL is that it is not a value. Not “this is a NULL value” but “this NULL is not a value.” Everything either is a value, or it isn’t. When something is a value, it is “1,” or “hello,” or “green,” or “\$5.00″ etc – but when something isn’t a value, it just isn’t anything at all. SQL represents “this has no value” by the special non-value NULL. When someone says “the NULL value,” one should mentally disagree, because there’s no such thing. NULL is the complete, total absence of any value whatsoever.

### What do you get when you compare a value to NULL?

Short answer: NULL. Every time. The result of comparing anything to NULL, even itself, is always, always NULL. A comparison to NULL is never true or false. Since NULL can never be equal to any value, it can never be unequal, either.

Sometimes people have difficulty understanding why a comparison to NULL can never be either true or false. Here’s an informal proof that may help:

Given the following predicates,

1. NULL is not a value
2. No value can ever be equal to a non-value

Here’s the proof by contradiction: Pretend for a moment that NULL is unequal to a value – say a real number, excluding infinity and negative infinity. I’ll choose an example number, say 5.

1. Assume that NULL <> 5.
2. That is, NULL <> 5 is a true expression (comparison operations are boolean, true or false).
3. That means “NULL < 5 or NULL > 5” is true, since I’m dealing with finite, real numbers; if it’s not equal, it must be bigger or smaller.
4. Therefore, there exists a real number equal to NULL; it’s either less than 5 or greater than 5.
5. That’s a contradiction, because I took it as a given that no value can be equal to NULL.

Therefore NULL is neither equal to a value nor unequal to it, so any comparison involving NULL is neither true nor false. The result of a comparison involving NULL is not a boolean value – it is a non-value. You just can’t compare something that exists with something that doesn’t exist.

It has to be this way, because if a comparison to a non-value had a defined value, every query could be rewritten to return a wrong result. It would be possible to transform expressions to equivalent expressions that gave the opposite answer, and so on.

### The correct way to write the queries

Instead of using boolean comparison operators such as less-than and greater-than, equal-to and not-equal-to, these queries must be written with the special comparison operator IS NULL:

select * from table where column is null;

select * from table where column is not null;

The IS NULL operator tests whether a value is null or not null, and returns a boolean.

### The truth is, I lied

I’m trying to write this article to help people understand how non-values work in queries, so I’m being generous with the truth.

Since computers only work with things that exist, non-existence isn’t really possible, so NULLs must internally be implemented as some value, somewhere – even if it’s a value that indicates another value isn’t a value (huh?).

I’m glossing over something about comparisons to NULL, too. NULLs result in tri-valued logic; booleans are no longer just TRUE and FALSE, but can be UNKNOWN, too. The result of comparing NULLs is UNKNOWN, which is not the same thing as NULL, but that’s just semantic differences and deep mathematical pondering, and doesn’t materially affect how you write queries.

MySQL, for example, implements UNKNOWN as NULL, though it it isn’t perfectly consistent about it – try these queries:

select unknown;
select null;
select true;
select false;
select null is unknown;
select false is null;
select true is null;
select unknown is null;

Just remember NULL is neither equal nor unequal to anything, and I promise you will always be safe. It’s no use to get really picky about the fine points of NULL versus UNKNOWN and all that.

### A puzzler with COUNT

Someone posted a comment on the MySQL manual page about extensions to the GROUP BY clause, and I think it’s interesting to discuss here. The query is a way to count subsets within a group:

select shoeStyle,
count(color) as Count,
count(color = 'red' OR NULL) as redCount,
count(color = 'green' OR NULL) as greenCount,
count(color = 'blue' OR NULL) as blueCount
from bowlingShoes
group by shoeStyle;

The comment’s author said “OR NULL is necessary, or you will just get a count of all rows in the group.” Why is this?

If the OR NULL is omitted, the result of the expression is a boolean, TRUE or FALSE, which are actual values. The COUNT function counts any value that exists, not whether something is TRUE or FALSE, so the query is behaving correctly.

On the other hand, the result of the expression color = 'green' OR NULL is either TRUE or NULL. Boolean expressions are short-circuited when they’re evaluated. As soon as the first sub-expression in a logical OR expression is true, the whole result is true, so when the color is green, the expression is TRUE immediately – a COUNT-able value. If the color isn’t green, the expression becomes FALSE OR NULL, which is NULL, of course – not a COUNT-able value.

You can see this in action with the following queries:

mysql> select true or null;
+--------------+
| true or null |
+--------------+
| 1            |
+--------------+
1 row in set (0.00 sec)

mysql> select false or null;
+---------------+
| false or null |
+---------------+
| NULL          |
+---------------+
1 row in set (0.00 sec)

I'm Baron Schwartz, the founder and CEO of VividCortex. I am the author of High Performance MySQL and many open-source tools for performance analysis, monitoring, and system administration. I contribute to various database communities such as Oracle, PostgreSQL, Redis and MongoDB.