SQL Cheat Sheet: Basic to Advanced

SQL (Structured Query Language) is the standard language used to interact with relational databases. It can create, read, update, and delete data (CRUD), shape results for reports, run analytics, and manage database objects like tables, indexes, views, etc.

SQL works on a declarative approach, which means you describe what you want, and the database figures out how to get it. Don’t you think it can be a great skill for you? Start learning with this SQL cheat sheet, explaining each operation from basic to advanced.

What is SQL?

SQL is a domain-specific language used to handle relational databases. It is too popular that you can see its application in almost every data-based tech. Think of it as a primary language you can use to interact with databases. It allows you to perform various operations on the data stored within them. It also provides different features, including:

• Query data (SELECT)

• Filter and aggregate (WHERE, GROUP BY, HAVING)

• Join tables (JOIN)

• Modify data (INSERT, UPDATE, DELETE)

• Define schema (CREATE/ALTER/DROP)

• Control transactions (BEGIN/COMMIT/ROLLBACK)

• Extend behavior with views, stored procedures, triggers, and window functions.

Different Dialects of SQL You Can Use

SQL has different database systems with small syntax differences and additional features. It is because of the variety in data and database types. You should be aware of all of them to become proficient in SQL. Some of the common SQL dialects are:

• MySQL/MariaDB - popular for web apps.

• PostgreSQL - known for standards compliance and advanced features (JSON, window functions).

• Microsoft SQL Server (T-SQL) - Microsoft’s extension; integrates with .NET ecosystems.

• Oracle (PL/SQL) - enterprise features and powerful procedural extensions.

• SQLite - lightweight, file-based DB for apps and testing.

• Amazon Redshift/Snowflake/BigQuery - analytical variants optimized for data warehousing (each has SQL dialect quirks).

Read Also: PostgreSQL Tutorial For Beginners in 2026

The SQL Cheat Sheet: Every Command You Should Use in 2026

The table given below includes all the commands and concepts, from basic to advanced, that you should know.

Examples of Using SQL: Basic to Advanced

Let’s explore some real-life examples to understand how to use SQL perfectly:

I. Basic Data Retrieval (SELECT Queries)

1. Select basics

SELECT id, name, email
FROM users;

2. Select all

SELECT *
FROM employees;

3. Filter (WHERE)

SELECT *
FROM orders
WHERE status = 'shipped';

4. Comparison operators

SELECT id, price
FROM products
WHERE price > 100 AND price <= 500;

5. Logical operators (AND, OR, NOT)

SELECT *
FROM events
WHERE (type = 'login' OR type = 'signup') AND active = TRUE;

6. IN / NOT IN

SELECT id, country
FROM customers
WHERE country IN ('IN', 'US', 'GB');

7. BETWEEN

SELECT order_id, created_at
FROM orders
WHERE created_at BETWEEN '2025-01-01' AND '2025-01-31';

8. LIKE

SELECT id, name
FROM users
WHERE name LIKE 'J%n';

9. IS NULL / IS NOT NULL

SELECT id, deleted_at
FROM posts
WHERE deleted_at IS NULL;

10. DISTINCT

SELECT DISTINCT department
FROM employees;

II. Aggregation & Grouping

11. Aggregate functions

SELECT COUNT(*) AS total_orders,
       SUM(total_amount) AS total_revenue,
       AVG(total_amount) AS avg_order
FROM orders;

12. GROUP BY

SELECT department, COUNT(*) AS headcount
FROM employees
GROUP BY department;

13. HAVING

SELECT department, COUNT(*) AS headcount
FROM employees
GROUP BY department
HAVING COUNT(*) > 10;

III. Sorting & Pagination

14. ORDER BY

SELECT id, created_at
FROM tickets
ORDER BY created_at DESC;

15. LIMIT / OFFSET

SELECT id, name
FROM products
ORDER BY id
LIMIT 10 OFFSET 20;

IV. Joins & Subqueries

16. JOINS (INNER / LEFT)

-- INNER JOIN
SELECT u.id, u.name, o.id AS order_id
FROM users u
JOIN orders o ON o.user_id = u.id;

-- LEFT JOIN
SELECT u.id, u.name, o.id AS order_id
FROM users u
LEFT JOIN orders o ON o.user_id = u.id;

17. Subqueries (scalar + table)

-- Scalar
SELECT id,
       (SELECT COUNT(*) FROM orders o WHERE o.user_id = u.id) AS order_count
FROM users u;

-- Table subquery
SELECT name
FROM (SELECT name FROM users WHERE active = TRUE) AS active_users;

18. EXISTS

SELECT u.id, u.name
FROM users u
WHERE EXISTS (
  SELECT 1 FROM orders o WHERE o.user_id = u.id AND o.status = 'completed'
);

19. UNION / UNION ALL

SELECT email FROM customers_us
UNION
SELECT email FROM customers_eu;

SELECT email FROM customers_us
UNION ALL
SELECT email FROM customers_eu;

V. Data Modification (DML)

20. INSERT

INSERT INTO users (name, email, signup_date)
VALUES ('Asha', 'asha@example.com', CURRENT_DATE);

21. INSERT … SELECT

INSERT INTO archive_events (id, event_data, archived_at)
SELECT id, event_data, NOW()
FROM events
WHERE created_at < '2024-01-01';

22. UPDATE

UPDATE users
SET last_login = NOW()
WHERE id = 42;

23. DELETE

DELETE FROM sessions
WHERE expires_at < NOW();

VI. Schema Definition (DDL)

24. CREATE TABLE

CREATE TABLE products (
  id SERIAL PRIMARY KEY,
  name VARCHAR(255),
  price NUMERIC(10,2),
  created_at TIMESTAMP DEFAULT NOW()
);

25. ALTER TABLE

ALTER TABLE users
ADD COLUMN bio TEXT;

26. DROP TABLE

DROP TABLE IF EXISTS temp_data;

27. CREATE INDEX

CREATE INDEX idx_orders_customer
ON orders(customer_id);

VII. Transactions & Database Control

28. Transactions (BEGIN / COMMIT / ROLLBACK)

BEGIN;
UPDATE accounts SET balance = balance - 100 WHERE id = 1;
UPDATE accounts SET balance = balance + 100 WHERE id = 2;
COMMIT;

29. Views

CREATE VIEW active_users AS
SELECT id, name
FROM users
WHERE active = TRUE;

30. Grant / Revoke

GRANT SELECT, INSERT ON sales TO sales_app;
REVOKE DELETE ON sales FROM junior_analyst;

VIII. Advanced SQL

31. Stored function (PostgreSQL example)

CREATE FUNCTION add_numbers(a INT, b INT)
RETURNS INT AS $$
BEGIN
  RETURN a + b;
END;
$$ LANGUAGE plpgsql;

32. Trigger

CREATE FUNCTION audit_user_insert() RETURNS TRIGGER AS $$
BEGIN
  INSERT INTO audit_log (user_id, action)
  VALUES (NEW.id, 'user_created');
  RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER trg_audit_user_insert
AFTER INSERT ON users
FOR EACH ROW EXECUTE FUNCTION audit_user_insert();

33. Common data types

CREATE TABLE sample (
  id BIGINT,
  name VARCHAR(100),
  profile JSONB,
  price NUMERIC(8,2),
  active BOOLEAN,
  created_at TIMESTAMP
);

34. Window functions

SELECT user_id, amount,
       SUM(amount) OVER (PARTITION BY user_id ORDER BY created_at) AS running_total,
       ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC) AS rn
FROM payments;

35. CASE expression

SELECT id, qty,
       CASE
         WHEN qty = 0 THEN 'Out of stock'
         WHEN qty < 5 THEN 'Low'
         ELSE 'In stock'
       END AS stock_status
FROM inventory;

36. EXPLAIN / EXPLAIN ANALYZE

EXPLAIN ANALYZE
SELECT * FROM huge_table WHERE customer_id = 123;

IX. Dialect-Specific Notes (Optional but Useful)

37. LIMIT vs TOP vs FETCH

-- MySQL/PostgreSQL
SELECT * FROM products ORDER BY id LIMIT 5;

-- SQL Server
SELECT TOP 5 * FROM products;

38. Auto-increment differences

-- PostgreSQL
CREATE TABLE t (id SERIAL PRIMARY KEY);

-- MySQL
CREATE TABLE t (id INT AUTO_INCREMENT PRIMARY KEY);

39. Date/time function differences

SELECT NOW();       -- Postgres/MySQL
SELECT GETDATE();   -- SQL Server

Wrap-Up

SQL remains one of the most essential skills in data, development, analytics, and backend engineering. Whether you’re filtering data, joining tables, writing reports, or managing large-scale databases, the commands you learned here form the foundation for everything you’ll do with SQL.

This SQL cheat sheet is designed to give beginners a complete, ready-to-use reference. It is something you can quickly scan before writing a query or preparing for an interview. As you continue learning, try running each example in a real database environment. The more you practice, the faster SQL will feel like second nature.

Read Also

• Top SQL MCQ With Answers

• How to Delete Duplicate Rows in SQL?

• How to Install Microsoft SQL Server?

• Top SQL Server Interview Questions and Answers

• What is RDBMS?

FAQs

1. Is SQL hard to learn for beginners?

Not really. With the declarative approach of SQL, you only need to tell the database what you want. So, anyone can learn it.

2. Which SQL dialect should I start with?

If you're just learning, start with MySQL or PostgreSQL. Both are free, widely used, and beginner-friendly. Once you learn the basics, switching between dialects becomes easy.

3. Can SQL be used for data science and analytics?

Yes, SQL is one of the most important skills for data analysts and data scientists. It’s used for data cleaning, filtering, aggregation, reports, and preparing datasets for machine learning.