Experimental Study on Improving SQL Query Performance using Indexing Techniques

Authors:

Dr. Suresh Kurumalla¹, Padidham Ashwitha²

¹Professor, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India kurumallaasuresh@gmail.com

 ²Student, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India ashwithapadidhan34@gmail.com

Abstract

This paper presents an experimental study on improving SQL query performance using indexing techniques. In modern applications, databases store large volumes of data, and retrieving this data efficiently is very important. When queries are executed without optimization, they often take more time because the database searches the entire table to find the required data. This results in slower system performance and poor user experience. To solve this problem, indexing is used as an effective technique. Indexing allows the database to locate data quickly without scanning every row in a table. This study focuses on analyzing how different types of indexing techniques can improve query execution time and overall performance. In this experiment, queries are executed on a database with and without indexes. The performance is measured based on execution time and efficiency. Various indexing strategies such as single-column indexing and multi-column indexing are applied and compared. The results show that indexing significantly reduces query execution time and improves performance, especially when working with large datasets. However, the study also highlights that excessive or improper use of indexing can increase storage usage and affect data modification operations like insert, update, and delete. This paper concludes that proper use of indexing techniques, along with optimized query design, plays a major role in enhancing database performance. The findings of this study can help developers and beginners understand how to improve SQL query efficiency in real-world applications.

Keywords: SQL, Indexing Techniques, Query Optimization, Database Performance, Clustered Index, Non-Clustered Index, Composite Index