SQL Cheat Sheet

SQL (Structured Query Language) is a Query language used for managing and manipulating relational databases databases. It allows users to interact with databases. SQL allows users to perform various tasks such as querying data, updating data, inserting new records, deleting records, creating and modifying database schemas, and managing permissions.

In this article, we will explore the ultimate SQL cheat sheet with the PDF, covering a wide range of SQL commands, Joins in SQL, CRUD Operations, SQL Trigger, SQL Transactions, and advanced topics to help master SQL effectively.

SQL Cheat Sheet

Create a Database in SQL

Explore this section to get hands on all the cheat sheet that help you in order to create a database in SQL.

1. CREATE DATABASE: Create a New Database

CREATE DATABASE company;

This command creates a new database named “company.”

2. USE: Select a Specific Database to Work With

USE company;

This command selects the database named “company” for further operations.

3. ALTER DATABASE: Modify a Database’s Attributes

ALTER DATABASE database_name

4. DROP DATABASE: Delete an Existing Database

DROP DATABASE company;

This command deletes the database named “company” and all its associated data.

Creating Data in SQL

Here in this SQL cheat sheet we have listed down all the cheat sheet that help to create, insert, alter data in table.

5. CREATE: Create a New Table, Database, or Index

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  first_name VARCHAR(50),
  last_name VARCHAR(50),
  department VARCHAR(50),
  salary DECIMAL(10, 2)
);

This command creates a table named “employees” with columns for employee ID, first name, last name, department, and salary. The employee_id column is set as the primary key.

6. INSERT INTO: Add New Records To A Table

INSERT INTO employees (employee_id, first_name, last_name, department, salary)
VALUES
  (1, 'John', 'Doe', 'HR', 50000.00),
  (2, 'Jane', 'Smith', 'IT', 60000.00),
  (3, 'Alice', 'Johnson', 'Finance', 55000.00),
  (4, 'Bob', 'Williams', 'IT', 62000.00),
  (5, 'Emily', 'Brown', 'HR', 48000.00);

This command inserts sample data into the “employees” table with values for employee ID, first name, last name, department, and salary.

7. ALTER TABLE: Modify An Existing Table’s Structure

ALTER TABLE employees
ADD COLUMN new_column INT;

This command adds a new column named “new_column” of integer type to the existing “employees” table.

8. DROP TABLE: Delete A Table And Its Data

DROP TABLE employees;

This command deletes the entire “employees” table along with all its data.

Reading/Querying Data in SQL

Explore this section to get the cheat sheet on how to use select, distinct and other querying data in SQL.

9. SELECT: Retrieve Data From One Or More Tables

SELECT * FROM employees;

This query will retrieve all columns from the employees table.

10. DISTINCT: Select Unique Values From A Column

SELECT DISTINCT department FROM employees;

This query will return unique department names from the employees table.

11. WHERE: Filter Rows Based On Specified Conditions

SELECT * FROM employees WHERE salary > 55000.00;

This query will return employees whose salary is greater than 55000.00.

12. LIMIT: Limit The Number Of Rows Returned In The Result Set

SELECT * FROM employees LIMIT 3;

This query will limit the result set to the first 3 rows.

13. OFFSET: Skip A Specified Number Of Rows Before Returning The Result Set

SELECT * FROM employees OFFSET 2;

This query will skip the first 2 rows and return the rest.

14. FETCH: Retrieve A Specified Number Of Rows From The Result Set

SELECT * FROM employees FETCH FIRST 3 ROWS ONLY;

This query will fetch the first 3 rows from the result set.

15. CASE: Perform Conditional Logic In A Query

SELECT 
  first_name,
  last_name,
  CASE 
    WHEN salary > 55000 THEN 'High'
    WHEN salary > 50000 THEN 'Medium'
    ELSE 'Low'
  END AS salary_category
FROM employees;

This query will categorize employees based on their salary into ‘High’, ‘Medium’, or ‘Low’.

Updating/Manipulating Data in SQL

Get a cheat sheet on how to update or manipulate data in SQL by exploring this section.

16. UPDATE: Modify Existing Records In A Table

UPDATE employees
SET salary = 55000.00
WHERE employee_id = 1;

This query will update the salary of the employee with employee_id 1 to 55000.00.

Deleting Data in SQL

17. DELETE: Remove Records From A Table

DELETE FROM employees
WHERE employee_id = 5;

This query will delete the record of the employee with employee_id 5 from the employees table.

Filtering Data in SQL

18. WHERE: Filter Rows Based On Specified Conditions

SELECT * FROM employees
WHERE department = 'IT';

This query will retrieve all employees who work in the IT department.

19. LIKE: Match A Pattern In A Column

SELECT * FROM employees
WHERE first_name LIKE 'J%';

This query will retrieve all employees whose first name starts with ‘J’.

20. IN: Match Any Value In A List

SELECT * FROM employees
WHERE department IN ('HR', 'Finance');

This query will retrieve all employees who work in the HR or Finance departments.

21. BETWEEN: Match Values Within A Specified Range

SELECT * FROM employees
WHERE salary BETWEEN 50000 AND 60000;

This query will retrieve all employees whose salary is between 50000 and 60000.

22. IS NULL: Match NULL Values

SELECT * FROM employees
WHERE department IS NULL;

This query will retrieve all employees where the department is not assigned (NULL).

23. ORDER BY: Sort The Result Set

SELECT * FROM employees
ORDER BY salary DESC;

This query will retrieve all employees sorted by salary in descending order.

SQL Operator

Here in this section we have added a cheat sheet for SQL Operators. So, explore and learn how to use AND, OR, NOT and others oprtators.

24. AND: Combines Multiple Conditions In A WHERE Clause

SELECT * FROM employees
WHERE department = 'IT' AND salary > 60000;

This query will retrieve employees who work in the IT department and have a salary greater than 60000.

25. OR: Specifies Multiple Conditions Where Any One Of Them Should Be True

SELECT * FROM employees
WHERE department = 'HR' OR department = 'Finance';

This query will retrieve employees who work in either the HR or Finance department.

26. NOT: Negates A Condition

SELECT * FROM employees
WHERE NOT department = 'IT';

This query will retrieve employees who do not work in the IT department.

27. LIKE: Searches For A Specified Pattern In A Column

SELECT * FROM employees
WHERE first_name LIKE 'J%';

This query will retrieve employees whose first name starts with ‘J’.

28. IN: Checks If A Value Matches Any Value In

SELECT * FROM employees
WHERE department IN ('HR', 'Finance');

This query will retrieve employees who work in the HR or Finance departments.

29. BETWEEN: Selects Values Within a Specified Range

SELECT * FROM employees
WHERE salary BETWEEN 50000 AND 60000;

This query will retrieve employees whose salary is between 50000 and 60000.

30. IS NULL: Checks if a Value is NULL

SELECT * FROM employees
WHERE department IS NULL;

This query will retrieve employees where the department is not assigned (NULL).

31. ORDER BY: Sorts the Result Set in Ascending or Descending Order

SELECT * FROM employees
ORDER BY salary DESC;

This query will retrieve all employees sorted by salary in descending order.

32. GROUP BY: Groups Rows that have the Same Values into Summary Rows

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

This query will group employees by department and count the number of employees in each department.

Aggregation Data in SQL

Get an hands in aggregation data in SQL. Here you will find cheat sheet for how to count numbers, sum of numbers and more.

33. COUNT: Count The Number Of Rows In A Result Set

SELECT COUNT(*) FROM employees;

This query will count the total number of employees.

34. SUM: Calculate The Sum Of Values In A Column

SELECT SUM(salary) FROM employees;

This query will calculate the total salary of all employees.

35. AVG: Calculate The Average Value Of A Column

SELECT AVG(salary) FROM employees;

This query will calculate the average salary of all employees.

36. MIN: Find the Minimum Value in a Column

SELECT MIN(salary) FROM employees;

This query will find the minimum salary among all employees.

37. MAX: Find the Maximum Value in a Column

SELECT MAX(salary) FROM employees;

This query will find the maximum salary among all employees.

38. GROUP BY: Group Rows Based on a Specified Column

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

This query will group employees by department and count the number of employees in each department.

39. HAVING: Filter Groups Based on Specified Conditions

SELECT department, AVG(salary) AS avg_salary
FROM employees
GROUP BY department
HAVING AVG(salary) > 55000;

This query will calculate the average salary for each department and return only those departments where the average salary is greater than 55000.

Constraints in SQL

Constraints in SQL act as data quality guardrails, enforcing rules to ensure accuracy, consistency, and integrity within your database tables.

40. PRIMARY KEY: Uniquely Identifies Each Record in a Table

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  first_name VARCHAR(50),
  last_name VARCHAR(50)
);

employee_id is designated as the primary key, ensuring that each employee record has a unique identifier.

41. FOREIGN KEY: Establishes a Relationship Between Two Tables

CREATE TABLE departments (
  department_id INT PRIMARY KEY,
  department_name VARCHAR(50)
);

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  first_name VARCHAR(50),
  last_name VARCHAR(50),
  department_id INT,
  FOREIGN KEY (department_id) REFERENCES departments(department_id)
);

department_id column in the employees table is a foreign key that references the department_id column in the departments table, establishing a relationship between the two tables.

42. UNIQUE: Ensures That All Values in a Column Are Unique

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  email VARCHAR(100) UNIQUE
);

email column must contain unique values for each employee.

43. NOT NULL: Ensures That a Column Does Not Contain NULL Values

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  first_name VARCHAR(50) NOT NULL,
  last_name VARCHAR(50) NOT NULL
);

first_name and last_name columns must have values and cannot be NULL.

44. CHECK: Specifies a Condition That Must Be Met for a Column’s Value

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  age INT CHECK (age >= 18)
);

age column must have a value of 18 or greater due to the CHECK constraint.

Joins in SQL

Explore different join types to seamlessly merge data from multiple tables in your SQL queries.

45. INNER JOIN: Retrieves Records That Have Matching Values in Both Tables

SELECT * FROM employees
INNER JOIN departments ON employees.department_id = departments.department_id;

This query will retrieve records from both the employees and departments tables where there is a match on the department_id column.

46. LEFT JOIN: Retrieves All Records from the Left Table and the Matched Records from the Right Table

SELECT * FROM employees
LEFT JOIN departments ON employees.department_id = departments.department_id;

This query will retrieve all records from the employees table and only the matching records from the departments table.

47. RIGHT JOIN: Retrieves All Records from the Right Table and the Matched Records from the Left Table

SELECT * FROM employees
RIGHT JOIN departments ON employees.department_id = departments.department_id;

This query will retrieve all records from the departments table and only the matching records from the employees table.

48. FULL OUTER JOIN: Retrieves All Records When There Is a Match in Either the Left or Right Table

SELECT * FROM employees
FULL OUTER JOIN departments ON employees.department_id = departments.department_id;

This query will retrieve all records from both the employees and departments tables, including unmatched records.

49. CROSS JOIN: Retrieves the Cartesian Product of the Two Tables

SELECT * FROM employees
CROSS JOIN departments;

This query will retrieve all possible combinations of records from the employees and departments tables.

50. SELF JOIN: Joins a Table to Itself

SELECT e1.first_name, e2.first_name
FROM employees e1, employees e2
WHERE e1.employee_id = e2.manager_id;

In this example, the employees table is joined to itself to find employees and their respective managers based on the manager_id column.

SQL Functions

In this section we have compiled SQL cheat sheet for SQL functions. It is used for common tasks like aggregation, filtering, date/time manipulation, and more!

51. Scalar Functions: Functions That Return a Single Value

SELECT UPPER(first_name) AS upper_case_name FROM employees;

This query uses the UPPER() scalar function to convert the first_name column values to uppercase.

52. Aggregate Functions: Functions That Operate on a Set of Values and Return a Single Value

SELECT AVG(salary) AS average_salary FROM employees;

This query uses the AVG() aggregate function to calculate the average salary of all employees.

53. String Functions: Functions That Manipulate String Values

SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM employees;

This query uses the CONCAT() string function to concatenate the first_name and last_name columns into a single column called full_name.

54. Date and Time Functions: Functions That Operate on Date and Time Values

SELECT CURRENT_DATE AS current_date FROM dual;

This query uses the CURRENT_DATE date function to retrieve the current date.

55. Mathematical Functions: Functions That Perform Mathematical Operations

SELECT SQRT(25) AS square_root FROM dual;

This query uses the SQRT() mathematical function to calculate the square root of 25.

Subqueries in SQL

This SQL cheat sheet explains how to nest queries for powerful data filtering and manipulation within a single statement.

56. Single-row Subquery: Returns One Row of Result

SELECT first_name, last_name
FROM employees
WHERE salary = (SELECT MAX(salary) FROM employees);

In this example, the subquery (SELECT MAX(salary) FROM employees) returns a single row containing the maximum salary, and it’s used to filter employees who have the maximum salary.

57. Multiple-row Subquery: Returns Multiple Rows of Result

SELECT department_name
FROM departments
WHERE department_id IN (SELECT department_id FROM employees);

In this example, the subquery (SELECT department_id FROM employees) returns multiple rows containing department IDs, and it’s used to filter department names based on those IDs.

58. Correlated Subquery: References a Column from the Outer Query

SELECT first_name, last_name
FROM employees e
WHERE salary > (SELECT AVG(salary) FROM employees WHERE department = e.department);

In this example, the subquery (SELECT AVG(salary) FROM employees WHERE department = e.department) is correlated with the outer query by referencing the department column from the outer query. It calculates the average salary for each department and is used to filter employees whose salary is greater than the average salary of their respective department.

59. Nested Subquery: A Subquery Inside Another Subquery

SELECT first_name, last_name
FROM employees
WHERE department_id IN (
    SELECT department_id
    FROM departments
    WHERE department_name = 'IT'
);

In this example, the subquery (SELECT department_id FROM departments WHERE department_name = ‘IT’) is nested within the outer query. It retrieves the department ID for the IT department, which is then used in the outer query to filter employees belonging to the IT department.

Views in SQL

Here in this SQL cheat sheet unveils how to create virtual tables based on existing data for streamlined access.

60. CREATE VIEW: Create a Virtual Table Based on the Result of a SELECT Query

CREATE VIEW high_paid_employees AS
SELECT *
FROM employees
WHERE salary > 60000;

This query creates a views named high_paid_employees that contains all employees with a salary greater than 60000.

61. DROP VIEW: Delete a View

DROP VIEW IF EXISTS high_paid_employees;

This query drops the high_paid_employees view if it exists.

Indexes in SQL

Speed up your SQL queries with our Indexes Cheat Sheet! Learn how to create and optimize indexes to dramatically improve database performance.

62. CREATE INDEX: Create an Index on a Table

CREATE INDEX idx_department ON employees (department);

This query creates an index named idx_department on the department column of the employees table.

63. DROP INDEX: Remove an Index

DROP INDEX IF EXISTS idx_department;

This query drops the idx_department index if it exists.

Transactions in SQL

Learn how to manage groups of database operations as a single unit for reliable data updates.

64. BEGIN TRANSACTION: Start a New Transaction

BEGIN TRANSACTION;

This statement starts a new transaction.

65. COMMIT: Save Changes Made During the Current Transaction

COMMIT;

This statement saves all changes made during the current transaction.

66. ROLLBACK: Undo Changes Made During the Current Transaction

ROLLBACK;

This statement undoes all changes made during the current transaction.

Advanced Mixed Data in SQL

In the last we have complied all the imprtant queries under the one advanced SQL cheat sheet.

67. Stored Procedures: Precompiled SQL Statements That Can Be Executed with a Single Command

CREATE PROCEDURE get_employee_count()
BEGIN
  SELECT COUNT(*) FROM employees;
END;

This query creates a stored procedure named get_employee_count that returns the count of employees.

68. Triggers: Automatically Execute a Set of SQL Statements When a Specified Event Occurs

CREATE TRIGGER before_employee_insert
BEFORE INSERT ON employees
FOR EACH ROW
BEGIN
  SET NEW.creation_date = NOW();
END;

This query creates a trigger named before_employee_insert that sets the creation_date column to the current date and time before inserting a new employee record.

69. User-defined Functions (UDFs): Custom SQL Functions Created by Users to Perform Specific Tasks

CREATE FUNCTION calculate_bonus(salary DECIMAL) RETURNS DECIMAL
BEGIN
  RETURN salary * 0.1; -- 10% bonus
END;

This query creates a user-defined function named calculate_bonus that calculates the bonus based on the salary.

70. Common Table Expressions (CTEs): Temporary Result Sets That Can Be Referenced Within a SELECT, INSERT, UPDATE, or DELETE Statement

WITH high_paid_employees AS (
  SELECT * FROM employees WHERE salary > 60000
)
SELECT * FROM high_paid_employees;

This query uses a common table expression named high_paid_employees to retrieve all employees with a salary greater than 60000.

SQL Cheat Sheet PDF

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Conclusion

SQL is a powerful and versatile language for managing and manipulating relational databases. This comprehensive cheat sheet covers a wide array of SQL commands and concepts, ranging from database creation to advanced topics like stored procedures, triggers, and user-defined functions. this cheat sheet serves as a valuable resource for both beginners looking to learn SQL fundamentals and experienced users seeking to enhance their proficiency and efficiency in database management and manipulation.