Understanding the Types of SQL Operators: Practical Examples and Best Practices

SQL operators are crucial for data manipulation, allowing tasks like filtering, comparisons, and calculations.

Types of SQL operators include arithmetic, logical, comparison, and bitwise operators in SQL like AND, OR, and XOR for binary operations. These operators streamline complex queries and improve database efficiency.

This article explains the types of SQL operators, their roles, and practical applications with detailed examples to enhance your query-building skills.

Different Types of SQL Operators

SQL operators form the base of data manipulation and querying, allowing precise and complex operations on data structures. They enable users to filter rows with comparison operators, combine datasets using logical operators, and perform calculations with arithmetic operators.

Advanced operations like pattern matching and bitwise logic further enhance their utility. Understanding these operators is crucial for writing optimized and functional SQL queries that effectively manipulate and analyze data.

This section explores the different types of SQL operators and provides practical examples to demonstrate their usage.

1. Arithmetic Operators in SQL

Arithmetic operators in SQL are used to perform mathematical operations on SQL data types. These operations are foundational for tasks that involve numerical calculations, such as financial computations or data transformations.

By using these operators, SQL queries can derive meaningful results, such as totals, averages, or differences, directly within the query. Here is a look at the common arithmetic operators:

Example:

Consider the following query that uses an arithmetic operator to adjust employee salaries:

SELECT employee_name, salary + 1000 AS new_salary FROM employees;

This query adds 1000 to each employee's salary, returning their updated salaries. Arithmetic operators can also be combined for more complex expressions, such as calculating bonus percentages or total revenue.

Also Read: SQL Jobs for Freshers: SQL Developer Salary, Growth, and Career Guide

With a basic understanding of arithmetic operations, let’s now explore comparison operators, which allow us to assess data relationships.

2. Comparison Operators in SQL

Comparison operators are integral for filtering data based on relational conditions.

These operators are used to compare two values or expressions and return boolean results (TRUE or FALSE).

They are essential for filtering data when performing queries, especially when determining if a row meets certain criteria or falls within a specific range.

Here is a quick look at the common comparison operators:

Example:

Consider a query that retrieves all employees whose salary is above 50,000:

SELECT * FROM employees WHERE salary >= 50000;

This query filters out employees whose salary is less than 50,000, returning only those who meet or exceed this threshold.

Comparison operators are especially useful when combined with logical operators, which allow for the evaluation of multiple conditions at once.

Also Read: SQL For Data Science: Why Or How To Master Sql For Data Science

Let’s examine how logical operators help you perform complex condition checks.

3. Logical Operators in SQL

Logical operators in SQL are used to combine multiple conditions, creating compound criteria for filtering data. They allow you to test whether one or more conditions are TRUE or FALSE. Logical operators are crucial for building complex queries where multiple conditions need to be checked simultaneously.

These operators enhance the flexibility of SQL queries, enabling more sophisticated filtering logic.

Here are the commonly used logical operators:

Example:

SELECT * FROM employees WHERE salary > 50000 AND age < 40;

This query returns employees who meet both conditions: earning more than 50,000 and being younger than 40. Logical operators allow for intricate filtering, enabling more tailored data retrieval.

Also Read: SQL Interview Questions and Answers for Beginners and Experienced Professionals

Now that you have seen how logical operators help to refine search conditions, let's explore bitwise operators, which operate at the binary level, offering another layer of data manipulation.

4. Bitwise Operators in SQL

Bitwise operators are used to manipulate binary data directly. These operators perform operations on individual bits of integer values, making them suitable for low-level programming tasks like flag settings, encryption, and binary data processing. While not as commonly used in general SQL queries, bitwise operators are indispensable in scenarios where direct bit manipulation is required.

Here are the most often-used Bitwise Operators:

Example:

SELECT (5 & 3) AS result;

This query applies the bitwise AND operation between the binary representations of 5 (0101) and 3 (0011), resulting in 0001, which is 1 in decimal.

Also Read: SQL Vs MySQL: Difference Between SQL and MySQL

Bitwise operators can be extremely useful in specialized applications. For more advanced assignments or manipulations, SQL also offers compound operators, which allow you to perform calculations and assignments in one step.

5. Compound Operators in SQL

Compound operators combine an operation with an assignment, streamlining common operations like addition, subtraction, and multiplication. These operators allow for concise updates and modifications to data within a table without requiring multiple lines of code. They are particularly helpful when working with large datasets or performing repetitive tasks.

Common compound operators include:

Example:

UPDATE employees SET salary += 1000 WHERE employee_id = 1;

This query adds 1000 to the salary of the employee with ID 1, making the operation both more efficient and readable.

Also Read: SQL vs Python: A Detailed Comparison

With the understanding of compound operators, let’s now move on to special operators, which provide unique ways to filter and compare data beyond the standard operations.

6. Special Operators in SQL

Special operators in SQL offer advanced capabilities for comparing, filtering, and performing subquery operations. These operators provide specific functionality that goes beyond basic comparisons, often used to check for conditions like membership in a set, existence of data, or value ranges.

Special operators include:

Example:

SELECT * FROM employees WHERE salary BETWEEN 30000 AND 50000;

This query retrieves employees whose salaries fall between the values of 30,000 and 50,000, utilizing the BETWEEN operator for an inclusive range check.

Special operators like IN, EXISTS, and BETWEEN allow SQL users to create more complex queries that cater to specific business needs. Understanding when and how to use these operators is key to efficiently querying large and complex databases.

Also Read: SQL vs PL/SQL: Difference Between SQL & PL/SQL

Understanding the different types of SQL operators provides the foundation for working with database management, but seeing these operators in practical examples showcases how they solve actual data challenges effectively.

Practical Examples of SQL Operators

Practical examples of SQL operators demonstrate how they simplify complex database tasks by making data filtering, grouping, and manipulation more precise. Whether it’s retrieving records based on specific conditions, combining data from multiple tables, or performing calculations directly within queries, SQL operators are essential tools for handling structured data.

These examples will show how different operators work together to solve real-world problems effectively.

1. Using Arithmetic Operators for Data Transformation

Arithmetic operators are frequently used to perform calculations on data. They allow us to derive new values based on existing data.

Example: Calculating the Total Bill After Tax for Customers in a Restaurant

In a restaurant, let's say there are table orders where the total is the pre-tax bill. Calculate the total bill after applying an 18% GST (Goods and Services Tax).

SELECT customer_name, total_amount, total_amount * 1.18 AS total_with_tax
FROM orders;

• Explanation: The total_amount * 1.18 operation increases the total bill by 18%, representing the GST.
• Output: A list of customer names, their original bill amounts, and the final amount after applying the tax.

Also Read: Top 10 Real-Time SQL Project Ideas: For Beginners & Advanced

2. Using Comparison Operators for Conditional Filtering

Comparison operators are essential for filtering data based on specific conditions like equality, greater than, or less than.

Example: Finding Orders With Amount Greater Than ₹1,000

We use the > operator to retrieve customers who placed orders above ₹1,000 in value.

SELECT customer_name, total_amount
FROM orders
WHERE total_amount > 1000;

• Explanation: This query filters out orders where the total amount is greater than ₹1,000.
• Output: Customers whose order values exceed ₹1,000.

Also Read: Top 25+ SQL Projects on GitHub You Should Explore in 2025

3. Combining Comparison and Logical Operators for Complex Filtering

You can combine multiple conditions using logical operators (AND, OR, NOT) to filter the data in a more refined way.

Example: Finding Customers Who Placed Orders Greater Than ₹1,000 and Are from Delhi

This query combines > comparison with AND logical operator to filter orders above ₹1,000 from customers located in Delhi.

SELECT customer_name, total_amount, city
FROM orders
WHERE total_amount > 1000 AND city = 'Delhi';

• Explanation: The AND operator ensures both conditions are met: the order amount is greater than ₹1,000, and the customer is from Delhi.
• Output: Customers from Delhi who placed orders exceeding ₹1,000.

4. Using Bitwise Operators for Data Manipulation

Bitwise operators are less common in standard queries but can be useful when working with flags or binary data.

Example: Managing Customer Preferences with Flags

Let's say there is a table for customers where the preferences_flag column stores different flags for customer preferences in binary format (e.g., 1 for vegetarian, 2 for non-vegetarian). Use bitwise operations to update these preferences.

-- Setting the 'vegetarian' flag (binary OR with 1)
UPDATE customers
SET preferences_flag = preferences_flag | 1
WHERE customer_name = 'Ravi';
-- Unsetting the 'non-vegetarian' flag (binary AND with NOT of 2)
UPDATE customers
SET preferences_flag = preferences_flag & ~2
WHERE customer_name = 'Priya';

• Explanation:
  • The first query sets the vegetarian flag for 'Ravi'.
  • The second query unsets the non-vegetarian flag for 'Priya'.
• Output: The preferences_flag values for Ravi and Priya are updated accordingly.

5. Combining Multiple Operators for Aggregation and Grouping

You can use multiple operators in conjunction with GROUP BY to group data and perform calculations like averages or sums.

Example: Average Order Amount and Count by City

This query calculates the average order amount and the total number of orders for each city where the total order amount exceeds ₹1,000.

SELECT city, AVG(total_amount) AS avg_order_amount, COUNT(order_id) AS total_orders
FROM orders
WHERE total_amount > 1000
GROUP BY city;

• Explanation:
  • The query filters orders above ₹1,000 and groups them by city.
  • It calculates the average order value and the total number of orders in each city.
• Output:

Also Read: Primary Key in SQL Database: What is, Advantages & How to Choose

6. Using Special Operators for Set Operations

SQL has special operators like IN, BETWEEN, and EXISTS that provide more flexibility for querying data.

Example: Finding Orders for Specific Customers

The IN operator helps filter customers who placed orders from a set of selected customer names.

SELECT customer_name, total_amount
FROM orders
WHERE customer_name IN ('Rajesh', 'Priya', 'Ravi');

• Explanation: The IN operator checks if the customer_name matches any of the names in the list.
• Output:

7. Using EXISTS for Subquery Validation

The EXISTS operator can be used with subqueries to check if there are any matching records in a related table.

Example: Checking If Customers Have Ordered More Than Once

This query uses EXISTS to verify if a customer has placed more than one order.

SELECT customer_name
FROM customers c
WHERE EXISTS (
    SELECT 1 FROM orders o 
    WHERE o.customer_id = c.customer_id 
    GROUP BY o.customer_id 
    HAVING COUNT(o.order_id) > 1
);

• Explanation: The subquery checks if the customer has more than one order. The EXISTS operator returns customers who meet the condition.
• Output:

These practical examples show how SQL operators can be combined to perform complex data manipulation and retrieval.

Also Read: 25+ SQL Project Ideas for Beginners with Source Code in 2025 | Build Your Portfolio

Learning the different types of SQL operators lays the groundwork for efficient data handling, but true expertise comes with guided learning and real-world application. This is where upGrad’s programs can help you transform foundational knowledge into career-ready skills.

How upGrad Can Enhance Your SQL Skills

To understand SQL and elevate your data career in 2025, it’s essential to go beyond the basics and understand advanced query optimization, data modeling, and database management. SQL isn’t just a tool for querying data—it’s the backbone of analytics and decision-making in every industry. 

upGrad’s tailored programs are designed to give you hands-on expertise in SQL and its real-world applications, equipping you with the skills to handle complex database systems confidently. 

Here are some of the top programs to enhance your growth:

• Executive Diploma in Data Science & AI
• Post Graduate Certificate in Data Science & AI (Executive)
• Master’s Degree in Artificial Intelligence and Data Science
• Executive Diploma in Machine Learning and AI

Connect with upGrad counselors or visit the nearest upGrad Career Center to explore programs tailored to your goals. Strengthen your SQL skills to solve real-world data challenges, optimize processes, and position yourself for success in the tech-driven future.

Boost your career with our popular Software Engineering courses, offering hands-on training and expert guidance to turn you into a skilled software developer.

Explore our Popular Software Engineering Courses

Master in-demand Software Development skills like coding, system design, DevOps, and agile methodologies to excel in today’s competitive tech industry.

In-Demand Software Development Skills

Stay informed with our widely-read Software Development articles, covering everything from coding techniques to the latest advancements in software engineering.

Read our Popular Articles related to Software