Performance Optimization of SAP HANA using AI-based Workload Predictions
Harikrishna Madathala, Balaji Barmavat, Srinivasa Rao Thumala · International Journal of Innovative Research in Science Engineering and Technology · 2023
This research paper explores the application of artificial intelligence (AI) techniques for optimizing the performance of SAP HANA databases through predictive workload analysis and dynamic resource allocation. SAP HANA, as an in-memory, column-oriented relational database management system, presents unique challenges in performance tuning due to its complex architecture and diverse workload patterns. We propose a novel framework that leverages machine learning models to predict future workloads and intelligently allocate resources in real-time. Our approach demonstrates significant improvements in query response times, resource utilization, and overall system throughput compared to traditional optimization techniques. The study also addresses implementation challenges and outlines future research directions in this rapidly evolving field.