Table of Contents
<>
vs. !=
in SQLIn SQL, filtering data based on inequality is essential for queries like "find all customers who are not from New York" or "list products not in a specific category." This guide covers all ways to use "not equal" operators in SQL, with practical examples and optimizations.
When working with SQL, filtering data is a fundamental task. The "not equal" operator helps exclude records that don’t match a specific condition.
Whether you're querying a database for customer records, product listings, or log data, knowing how to use "not equal" efficiently can make your queries more precise.
SQL supports two main operators for "not equal":
<>
(Standard SQL, works in most databases)
!=
(Alternative syntax, but not supported in all databases)
Example:
-- Using <>
SELECT * FROM employees WHERE department <> 'HR';
-- Using !=
SELECT * FROM employees WHERE department != 'HR';
Note: While both work in MySQL and PostgreSQL, <>
is more widely supported.
<>
vs. !=
in SQLOperator | Compatibility | Preferred Usage |
---|---|---|
<> |
Works in all major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle) | Best for cross-database queries |
!= |
Works in most databases but may fail in some (e.g., older versions) | Common in MySQL & PostgreSQL |
Best Practice: Stick with <>
for maximum compatibility.
SELECT product_name, price
FROM products
WHERE price <> 100; -- Excludes products priced at $100
SELECT * FROM customers
WHERE country <> 'USA'; -- Finds customers outside the USA
SELECT * FROM orders
WHERE status <> 'Cancelled'
AND order_date > '2025-01-01';
Using NOT
with =
instead of <>
-- Less efficient
SELECT * FROM users WHERE NOT (status = 'inactive');
-- Better
SELECT * FROM users WHERE status <> 'inactive';
Forgetting NULL Values
<>
does not match NULL values. Use IS NOT NULL
instead.
SELECT * FROM employees
WHERE department <> 'HR' OR department IS NULL;
Index Usage: <>
can sometimes prevent index usage. For better performance, structure queries to use equality (=
) where possible.
Alternatives: For large datasets, consider NOT IN
or NOT EXISTS
for complex exclusions.
<>
the same as !=
?Yes, functionally they do the same thing, but <>
is more widely supported.
<>
work with NULL values?No, use IS NOT NULL
to filter NULLs.
!=
?Older databases like some versions of SQLite may not support !=
.
Mastering the SQL "not equal" operator (<>
or !=
) helps you write more flexible queries. Remember:
✔ Use <>
for better compatibility.
✔ Handle NULL values separately.
✔ Optimize queries for performance.
Now you're ready to filter data like a pro!