ADVANCED STRATEGIES TO ENHANCE QUERY PERFORMANCE IN RDBMS

Abstract

Optimizing queries is crucial for maintaining the high efficiency of Relational Database Management Systems (RDBMS). As data sizes expand and application demands grow, conventional optimization methods often fail to deliver optimal performance. This paper investigates contemporary approaches to improve query optimization, such as cost-based strategies, machine learning integration, adaptive query techniques, and innovative indexing mechanisms. A comparative evaluation between traditional and modern approaches is presented, highlighting existing challenges and suggesting future pathways to develop faster, more intelligent database systems.