Query Optimization Techniques in SQL: A Performance-Driven Perspective

Abstract

In the era of data-intensive applications, query optimization has become a cornerstone of efficient data management and retrieval in SQL-based systems. As organizations increasingly rely on relational databases for real-time analytics, business intelligence, and transactional operations, the need for high-performance query execution is more pressing than ever. This paper explores a wide array of query optimization techniques in SQL from a performance-driven perspective. It examines the theoretical and practical aspects of query planning and execution, including indexing strategies, join optimizations, subquery transformations, and cost-based optimization models. The discussion also includes the role of query execution plans, statistics, and advanced features such as materialized views and query caching. Through a performance-oriented lens, the paper illustrates how systematic optimization can dramatically reduce latency, resource consumption, and cost, especially in large-scale, distributed, or cloud-native database environments.