Optimizing SQL Query Performance in Spring Boot Applications: Best Practices and Techniques

Abstract

Modern applications heavily depend on relational databases for storing and managing structured data. In backend systems developed using frameworks such as Spring Boot, the efficiency of database interactions has a significant impact on overall system performance. Poorly designed SQL queries may lead to higher response time, higher server load, and inefficient utilization of resources.

This study focuses on exploring different techniques to improve SQL query performance in Spring Boot applications. Including issues such as the N+1 query problem, inefficient joins, lack of proper indexing, and redundant data retrieval. Various optimization strategies, including indexing, query restructuring, pagination, caching mechanisms, and connection pooling, are examined in detail.

The research also highlights the importance of using performance monitoring tools such as SQL execution plans and Hibernate statistics to detect inefficiencies. The results indicate that applying these techniques improves system performance noticeably and response time. The study concludes that careful query design is essential for building scalable and efficient backend applications.