Evaluating the Economics of Running SAP HANA
Key Takeaways
⇨ Lenovo ThinkSystem servers offer a lower total cost of ownership (TCO) over three years compared to Dell PowerEdge and HPE ProLiant servers for SAP HANA deployments, particularly in two-socket and four-socket configurations.
⇨ In-memory databases like SAP HANA are crucial for real-time analytics and transactional applications, with Lenovo's hardware reliability, support, and management features providing additional qualitative benefits.
⇨ Considerations for deploying SAP HANA in the cloud versus on-premises vary, with factors like cost savings, security, and regulatory requirements influencing the decision.
Businesses rely on transactional databases for a single source of truth. Organizations of all sizes need to extract insights from these very large databases. Housing these databases in memory can speed results and increase competitiveness. And while the price of memory continues to decline, single-unit scale-up servers still represent a sizable investment for IT organizations. However, the price of acquisition is only part of the cost; SAP HANA®
deployments can be expensive to operate, particularly when labor costs for the specialists to manage them are factored in. Prowess Consulting evaluated scale-up systems in a variety of memory configurations for SAP HANA solutions running on servers powered by the latest-generation Intel® Xeon® Scalable processors from Dell Technologies, HPE, and Lenovo. Our analysis shows that Lenovo® ThinkSystem™ SR650 V3 servers provide a lower total cost of ownership (TCO) over a three-year period among two-socket servers, compared to Dell™ PowerEdge™ R760 and HPE® ProLiant® DL380 Gen11 servers.
This lower TCO stems from both lower capital expenditures (CapEx) and lower operating expenses (OpEx) for the Lenovo® servers—but especially from the latter. In addition to raw TCO advantages, the Lenovo solutions for SAP HANA evaluated in this study also feature faster times to load databases into memory and perform complex queries than their counterparts from Dell Technologies and HPE while providing the same high degree of reliability as other Lenovo servers.
Real-time analytics is a primary operational requirement for enterprises. In-memory database platforms like the SAP HANA platform are the bedrock for this requirement, and they can also act as transactional databases for business applications, including finance, human resources (HR), order-to-cash, inventory, and forecasting applications. Running large databases in memory—even databases that are several terabytes in size—can keep storage latency from slowing down queries, providing faster, more actionable insights on a single source of truth for analytics and transactions, even as datasets grow increasingly large.
