SQL guide · Filtering

SQL WHERE: Filter Rows by a Condition

The WHERE clause limits which rows a statement works on. After the database has located the rows in the FROM table, it evaluates the condition in WHERE for each row and keeps only the rows for which the condition is true. Every other row is discarded before grouping, sorting or returning results.

WHERE is not limited to SELECT. The same clause decides which rows an UPDATE changes and which rows a DELETE removes, which makes it the single most important safety control in data-changing statements. A missing WHERE on an UPDATE rewrites the whole table.

Conditions are built from comparison operators (=, <>, <, >, <=, >=), and can be combined with AND, OR and NOT, or written with helpers such as IN, BETWEEN, LIKE and IS NULL. Columns used in WHERE are the usual candidates for an index, so a well written condition is also the main lever for query speed.

Basic syntax

SELECT column1, column2
FROM table_name
WHERE condition;

UPDATE table_name SET column1 = value WHERE condition;
DELETE FROM table_name WHERE condition;

The condition is any expression that evaluates to true, false or unknown. Only rows where it is true are kept, so a comparison against NULL (which yields unknown) removes the row. Aggregates such as SUM() cannot appear in WHERE; use HAVING for conditions on grouped results.

SQL WHERE examples

Filter on a single value

The simplest condition compares a column to a literal. Text and date literals go in single quotes, numbers do not. This returns only the customers located in Germany.

SELECT customer_id, name, city
FROM customers
WHERE country = 'Germany';

Combine several conditions

Use AND when every condition must hold and OR when any one is enough. Parentheses make the grouping explicit, which matters because AND is evaluated before OR. Here we want recent orders that are either large or flagged as priority.

SELECT order_id, customer_id, total, order_date
FROM orders
WHERE order_date >= '2026-01-01'
  AND (total > 500 OR is_priority = 1);

Use WHERE in an UPDATE

The clause controls which rows change. This statement applies a price increase only to products in one category and leaves everything else alone. Running the matching SELECT first is a cheap way to preview the affected rows.

UPDATE products
SET price = price * 1.05
WHERE category = 'Accessories';

Filter with a subquery

The right side of a comparison can come from another query. This returns employees paid more than the company average. The subquery runs once and returns a single value.

SELECT employee_id, name, salary
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);

Where SQL dialects differ

PostgreSQL: String comparisons with = are case sensitive, and LIKE is too. Use ILIKE for case-insensitive matching. Boolean columns can be used directly, as in WHERE is_active.

MySQL: With the default collations (such as utf8mb4_0900_ai_ci, the default since 8.0) string comparison is case insensitive, so WHERE name = 'smith' also matches Smith. Double quotes may be read as string literals unless ANSI_QUOTES is set.

SQL Server: Case sensitivity depends on the database collation, and the default collations are case insensitive. There is no boolean type, so write WHERE is_active = 1 rather than WHERE is_active.

SQLite: Comparisons use the column type affinity and are case sensitive for = by default, while LIKE is case insensitive for ASCII. Booleans are stored as 0 and 1.

Common mistakes

  • Forgetting WHERE on UPDATE or DELETE, which affects every row. Always write and test the filter as a SELECT first.
  • Testing for NULL with = NULL. The result is unknown, never true, so no rows match. Use IS NULL instead.
  • Mixing AND and OR without parentheses. AND binds tighter, so a OR b AND c means a OR (b AND c), which is often not what was intended.
  • Putting an aggregate such as COUNT(*) > 5 in WHERE. Aggregates are computed after filtering, so the condition belongs in HAVING.
  • Wrapping an indexed column in a function, as in WHERE YEAR(order_date) = 2026. This usually prevents index use; compare the raw column against a date range instead.

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