Editorial Team · on 13 June 2026 · 7 min read · Last reviewed 13 June 2026

SQL (Structured Query Language) is a standardized programming language designed for managing and manipulating relational databases, enabling users to perform data retrieval, insertion, updating, and deletion operations.

Key facts

• SQL is pronounced either “ess-que-el” or “sequel.”
• The SQL standard is maintained by the ISO and IEC, with the current version being SQL:2016.
• SQL is widely used in data-driven applications, data analysis, and reporting tools.
• Popular relational database management systems that use SQL include MySQL, PostgreSQL, Oracle Database, and Microsoft SQL Server.

How do SELECT queries work in SQL?

A SELECT query is the most fundamental SQL operation, used to retrieve data from one or more tables in a relational database. The basic syntax of a SELECT query is as follows:

Clause	Description
SELECT	Specifies the columns to retrieve.
FROM	Indicates the table(s) from which to retrieve the data.
WHERE	(Optional) Filters the results based on specified conditions.
ORDER BY	(Optional) Sorts the results in ascending or descending order.

A simple SELECT query looks like this:

SELECT column1, column2 FROM table_name;

How can you filter data using SELECT queries?

To filter data in a SELECT query, you use the WHERE clause. The WHERE clause allows you to specify conditions that the returned rows must meet. These conditions can be simple comparisons, range conditions, or even complex logical expressions.

For example, to retrieve only the rows where the value in the “age” column is greater than 18, you would use the following query:

SELECT * FROM users WHERE age > 18;

You can also use the WHERE clause with logical operators such as AND, OR, and NOT to create more complex conditions. For instance, to retrieve rows where the “age” is greater than 18 and the “status” is ‘active’, you would use:

SELECT * FROM users WHERE age > 18 AND status = 'active';

Additionally, you can use the IN operator to specify a range of values for a column. For example, to retrieve rows where the “status” is either ‘active’ or ‘inactive’, you would use:

SELECT * FROM users WHERE status IN ('active', 'inactive');

To filter data based on patterns, you can use the LIKE operator with wildcards. For example, to retrieve rows where the “last_name” starts with ‘S’, you would use:

SELECT * FROM users WHERE last_name LIKE 'S%';

How do you sort and group data with SELECT queries?

To sort the results of a SELECT query, you use the ORDER BY clause. This clause allows you to sort the results in ascending or descending order based on one or more columns.

For example, to retrieve all rows from the “users” table and sort them by the “last_name” column in ascending order, you would use the following query:

SELECT * FROM users ORDER BY last_name ASC;

To sort the results in descending order, you would use:

SELECT * FROM users ORDER BY last_name DESC;

You can also sort by multiple columns. For instance, to sort the “users” table by “last_name” in ascending order and then by “first_name” in descending order, you would use:

SELECT * FROM users ORDER BY last_name ASC, first_name DESC;

To group data in a SELECT query, you use the GROUP BY clause. This clause groups rows that have the same values in specified columns into aggregated data. You can use aggregate functions like COUNT, SUM, AVG, MAX, and MIN with the GROUP BY clause to perform calculations on each group.

For example, to retrieve the total number of users for each “status” value in the “users” table, you would use the following query:

SELECT status, COUNT(*) FROM users GROUP BY status;

You can also use the HAVING clause to filter groups based on aggregate functions. For example, to retrieve only the groups with more than 10 users, you would use:

SELECT status, COUNT(*) FROM users GROUP BY status HAVING COUNT(*) > 10;

How do you join tables with SELECT queries?

Joins are used in SQL to combine rows from two or more tables based on a related column between them. This allows you to retrieve data from multiple tables in a single query. There are several types of joins, including INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

An INNER JOIN returns only the rows that have matching values in both tables. For example, to retrieve all rows from the “users” and “orders” tables where the “user_id” in the “orders” table matches the “id” in the “users” table, you would use:

SELECT users.*, orders.* FROM users INNER JOIN orders ON users.id = orders.user_id;

A LEFT JOIN returns all rows from the left table (the table mentioned first), and the matched rows from the right table. If there is no match, the result is NULL on the right side. For example, to retrieve all rows from the “users” table and the matched rows from the “orders” table, you would use:

SELECT users.*, orders.* FROM users LEFT JOIN orders ON users.id = orders.user_id;

Types of Joins

Join Type	Description	Example
INNER JOIN	Returns only the rows that have matching values in both tables.	SELECT users.*, orders.* FROM users INNER JOIN orders ON users.id = orders.user_id;
LEFT JOIN	Returns all rows from the left table and the matched rows from the right table. If there is no match, the result is NULL on the right side.	SELECT users.*, orders.* FROM users LEFT JOIN orders ON users.id = orders.user_id;
RIGHT JOIN	Returns all rows from the right table and the matched rows from the left table. If there is no match, the result is NULL on the left side.	SELECT users.*, orders.* FROM users RIGHT JOIN orders ON users.id = orders.user_id;
FULL JOIN	Returns all rows when there is a match in either the left or right table. If there is no match, the result is NULL on the side where there is no match.	SELECT users.*, orders.* FROM users FULL JOIN orders ON users.id = orders.user_id;

What are some best practices for writing SELECT queries?

When writing SELECT queries, it is essential to follow best practices to ensure optimal performance and readability. Some of these best practices include:

• Use explicit column names: Instead of using SELECT * to retrieve all columns, specify the columns you need. This can improve performance and make your queries more readable.
• Use table aliases: When working with multiple tables, use table aliases to make your queries more concise and easier to read.
• Use proper indexing: Ensure that your database tables have the appropriate indexes to speed up query performance. Indexes can significantly improve the speed of SELECT queries.
• Limit the use of functions in WHERE clauses: Using functions in WHERE clauses can prevent the use of indexes, leading to slower query performance. If possible, avoid using functions in WHERE clauses.
• Use JOINs instead of subqueries: JOINs are often more efficient than subqueries for combining data from multiple tables. Use JOINs whenever possible to improve query performance.
• Limit the result set: Use the LIMIT clause to limit the number of rows returned by a query. This can improve performance and reduce the amount of data transferred between the database and the application.

Mastering SELECT queries is a crucial skill for any developer or data analyst working with relational databases. By understanding the basics of SELECT queries and following best practices, you can write efficient and effective queries to retrieve the data you need. Always remember to optimize your queries for performance and readability, and stay updated with the latest SQL features and best practices.

SQL Query Optimization Techniques

Technique	Description
Use indexes	Create indexes on columns that are frequently used in WHERE clauses, JOIN conditions, and ORDER BY clauses to speed up query performance.
Avoid SELECT *	Specify the columns you need instead of using SELECT * to reduce the amount of data retrieved and improve performance.
Use JOINs instead of subqueries	JOINs are often more efficient than subqueries for combining data from multiple tables. Use JOINs whenever possible to improve query performance.
Limit the result set	Use the LIMIT clause to limit the number of rows returned by a query. This can improve performance and reduce the amount of data transferred between the database and the application.
Use EXPLAIN to analyze queries	The EXPLAIN command can help you understand how the database executes your queries and identify potential performance issues.

For more advanced SQL techniques, consider exploring topics like , , and . Additionally, familiarize yourself with the specific features and optimizations available in your database management system, such as or .

Frequently asked questions

What is a basic SELECT query structure?

A basic SELECT query starts with SELECT to specify columns, followed by FROM to name the table. For example: SELECT column1, column2 FROM table1. You can use SELECT * to retrieve all columns. Always specify columns explicitly to avoid unnecessary data retrieval and improve performance.

How do I filter data in a SELECT query?

Use the WHERE clause to filter data. For instance, SELECT * FROM employees WHERE department = 'Sales' retrieves only sales employees. You can combine conditions with AND, OR, and NOT. For example, WHERE salary > 50000 AND department = 'Sales' filters employees earning over $50,000 in the Sales department.

What is the purpose of the ORDER BY clause?

ORDER BY sorts query results. Use it to arrange data in ascending (default) or descending order. For example, SELECT * FROM products ORDER BY price DESC lists products from highest to lowest price. You can sort by multiple columns, e.g., ORDER BY category ASC, price DESC, to sort by category first, then price.

How do I group data in a SELECT query?

Use GROUP BY to group rows with identical values. For example, SELECT department, COUNT(*) FROM employees GROUP BY department shows employee counts per department. Combine with aggregate functions like SUM, AVG, or MAX to perform calculations on grouped data. For instance, SELECT department, AVG(salary) FROM employees GROUP BY department calculates average salaries by department.