SAP HANA Workload Management: A Comprehensive Study on Workload Classes

This study investigates workload management challenges in SAP HANA’s in-memory columnar storage, specifically focusing on the complexities of handling mixed OLTP and OLAP workloads. Traditional database management approaches often fail to address SAP HANA’s unique architecture, which combines high-speed transaction processing with real-time analytics. Drawing on research into mixed workload optimization (May et al., 2015) and SAP HANA’s architectural evolution (Färber et al., 2017), this paper explores workload throttling, prioritization, and real-time monitoring strategies to optimize resource allocation. Our findings offer practical guidance for database administrators managing critical business applications with high data demands, such as finance and supply chain. Additionally, we examine tools and techniques for performance tracing in third party applications like Tableau (Tableau Software, 2023), providing an integrated perspective on maintaining optimal SAP HANA performance under peak load conditions.

Authors

Publication Details

Journal
International Journal of Computer Trends and Technology
Published
2024-11-30
DOI
https://doi.org/10.14445/22312803/ijctt-v72i11p105
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
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article

SAP HANA Workload Management: A Comprehensive Study on Workload Classes

Puneet Aggarwal, Amit Aggarwal
International Journal of Computer Trends and Technology
Cloud Computing and Resource Management
article

SAP HANA Workload Management: A Comprehensive Study on Workload Classes

Puneet Aggarwal, Amit Aggarwal
article en

Abstract

This study investigates workload management challenges in SAP HANA’s in-memory columnar storage, specifically focusing on the complexities of handling mixed OLTP and OLAP workloads. Traditional database management approaches often fail to address SAP HANA’s unique architecture, which combines high-speed transaction processing with real-time analytics. Drawing on research into mixed workload optimization (May et al., 2015) and SAP HANA’s architectural evolution (Färber et al., 2017), this paper explores workload throttling, prioritization, and real-time monitoring strategies to optimize resource allocation. Our findings offer practical guidance for database administrators managing critical business applications with high data demands, such as finance and supply chain. Additionally, we examine tools and techniques for performance tracing in third party applications like Tableau (Tableau Software, 2023), providing an integrated perspective on maintaining optimal SAP HANA performance under peak load conditions.

International Journal of Computer Trends and TechnologyVol. 72(11)
Decent work and economic growth
Openalex Percentile: Top 58%
Cloud Computing and Resource Management
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