Benchmarking SQL Query Optimization Techniques Across Major RDBMS PlatformsBenchmarking SQL Query Optimization Techniques Across Major RDBMS Platforms

Abstract

SQL query optimization is central to RDBMS performance, impacting responsiveness, scalability, and resource efficiency. This study benchmarks optimization techniques across Oracle, SQL Server, PostgreSQL, MySQL, and IBM Db2, beginning with theoretical foundations such as cost models, equivalence rules, and statistical usage. It then examines platform-specific strategies, including adaptive query execution, advanced indexing, and machine learning-driven optimization. Using TPC-H and TPC-DS benchmarks, the analysis evaluates optimizer performance under standardized workloads, revealing both shared reliance on cost-based optimization and unique innovations per system. Emerging trends workload-aware cloud optimization, hybrid transactional/analytical processing, and energy-efficient query planning, underscore the evolving landscape, while benchmarking remains essential for system selection, tuning, and guiding research advancements.