AI-Driven Database Performance Tuning: Automated Indexing and Query Optimization

Abstract

Database performance tuning is crucial for ensuring the efficient operation of database systems, particularly in high-load environments. Traditional performance tuning techniques, while effective, often require significant manual intervention and expertise. This paper explores the application of Artificial Intelligence (AI) in automating database performance tuning, focusing on automated indexing and query optimization. We propose a framework that leverages AI techniques to enhance performance tuning processes, reduce manual effort, and improve overall database efficiency. Our approach includes a review of existing methodologies, the introduction of AI-driven techniques, and an evaluation of their effectiveness through experimental results.