Enhancing SQL Server Performance in Azure Environments through Intelligent Query Processing and Automated Index Maintenance

Abstract Recent innovations in Microsoft SQL Server and Azure SQL Database have introduced fine-grained configuration options, automated tuning, and intelligent query processing features. These enhancements empower database administrators to maintain optimal performance in dynamic cloud-based environments. This paper explores the synergy between index maintenance, statistical accuracy, and automated tuning in SQL Server and Azure SQL. It presents a scenario-based approach to resolving major performance issues and includes a review of recent literature to support best practices in performance tuning.