Performance Now, Capacity for the Future: Intel IT Tests SAP HANA* 2

For efficiency and growth, companies need data like humans need oxygen. All companies, including Intel, are being transformed by next-gen analytics and the data that fuels them. The analytics engines required at scale are a major investment, and architectural decisions have multi-year, multi-million-dollar implications.

Transforming our supply chain with faster analytics

As we digitally transform from a PC centric to a data centric company, increasing the speed to insights is imperative to maintain a competitive advantage. Intel’s supply chain is complex and requires making rapid, data-driven decisions to optimize order taking, resource procurement, manufacturing, testing, and final delivery of products.

Intel IT uses SAP HANA* 2 to operate, optimize, and innovate within its global supply chain, and as customer zero, we are tasked with transforming our legacy systems with the latest technology. For that reason, Intel IT recently compared our current SAP HANA 2 finance analytics cluster comprised of three 4-year-old servers, versus a single server based on 2nd Gen Intel® Xeon® Scalable processors and new Intel® Optane™ DC persistent memory. Each older server has 2 terabytes of DRAM, for a total of 6 terabytes of memory. The new single server was configured with 1.5 terabytes of DRAM and 3 terabytes of Intel Optane DC persistent memory, for a total of 4.5 terabytes of memory. This one new server, with less total memory, delivered 2.4X better performance and faster answers to our business questions.1

Increasing memory capacity for the future

Intel IT also evaluated refresh of our SAP HANA 2 landscape, or path to production, which includes servers for lab, development and QA, benchmarking, production, disaster recovery and production support.  We looked at two likely scenarios: a scale out cluster with 21 4-socket servers and 63 terabytes of memory, or a scale-up cluster with eight 8-socket servers and 96 terabytes of memory. The scale-up cluster provides 52% more in-memory capacity, giving us capacity for future data growth at lower cost.2

Intel and SAP collaborated for almost seven years to enable HANA and Intel Optane DC persistent memory. Intel IT’s findings demonstrate the payoff of our partnership—in better performance, as well as in increased capacity and lower total cost of ownership.

Learn more about Intel IT’s supply chain transformation in the white paper “Transforming Intel’s Supply Chain with Real-Time Analytics.”

1 2.4x better runtime performance:

Performance results are based on testing as of 03/4/19 and may not reflect all publicly available security updates. No product or component can be absolutely secure. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information visit

System configurations:

Baseline: three-node (1-master + 2-slave) SAP HANA® 2 scale-out configuration. Per node: 4 x Intel® Xeon® processor E7-8880 v3 (2.3 GHz, 150 W, 18 cores), CPU sockets: 4; Microcode:0x400001c; RAM capacity: 64 x 32 GB DIMM, RAM model: DDR4 2,133 Mbps; storage: GPFS*, approximately 21.8 TB of formatted local storage per node, SAN storage for backup space only; network: redundant 10 gigabit
Ethernet (GbE) network for storage and access, redundant 10G network for node-to-node; OS: SUSE* 12 SP2, SAP HANA®: 2.00.035, GPFS*: Average time of 50 individual test queries executed 30–50 times each, for a total of approximately 25,000 steps: 2.81 seconds.

New configuration: one master node SAP HANA® 2 scale-up configuration: CPU: 4 x 2nd Generation Intel® Xeon® Platinum 8260 processor (2.2 GHz, 165 W, 24 cores), CPU sockets: 4; Microcode: 0x400001c, RAM capacity: 24 x 64 GB DIMM, RAM model: DDR4 2,133 Mbps; Intel® Optane™ DC persistent memory: 24 x 126 GB PMM; storage: XFS*, 21 TB; network: redundant 10 GbE network; OS: SUSE* 15, SAP HANA®: 2.00.035, Intel® BKC: WW06. Average time of 50 individual test queries executed 30–50 times each, for a total of approximately 25,000 steps: 1.13 seconds.

2 52% more data capacity at same or lower cost:

Pricing guidance as of March 15, 2019. Intel does not guarantee any costs or cost reduction. Results have been estimated by Intel IT as of 3/4/2019 using internal Intel analysis or architecture simulation or modeling, and provided to you for informational purposes. Any differences in your system hardware, software or configuration may affect your actual results. Cost reduction scenarios described are intended as examples of how a given Intel- based product, in the specified circumstances and configurations, may affect future costs and provide cost savings. Circumstances will vary. Intel does not guarantee any costs or cost reduction. 

Scale-up configuration: 8-node SAP HANA® 2 landscape. Per node: 8-socket 2nd Generation Intel® Xeon® Platinum 8276M processors. Memory capacity per socket: 6 x 128 GB DDR4 2,133 MHz. and 6 x128 GB Intel® Optane™ DC persistent memory. Estimated total cost is $2,369,496. Estimated cost per server is $296,187 (CPU=$93,776; memory=$119,808; storage=$45,000; other=$37,603).

Scale-out configuration: 21-node SAP HANA® 2 landscape. Per node: 4-socket 2nd Generation Intel® Xeon® Platinum 8276 processor. Memory capacity per socket: 12 x 64 GB DDR4 2, 133 MHz. Estimated total cost is $2,834,433. Estimated cost per server is $134,973 (CPU=$34,876; memory=$33,994; storage=$21,000; other=$45,103).

Intel technologies may require enabled hardware, specific software, or services activation. Check with your system manufacturer or retailer.

Intel, the Intel logo, Intel Optane, and Xeon are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.

SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see for additional trademark information and notices.

*Other names and brands may be claimed as the property of others.

Published on Categories Analytics, Big Data and AnalyticsTags , , , , ,
Aziz Safa

About Aziz Safa

Aziz M. Safa, Chief Data Officer, Vice President of Information Technology, and General Manager Enterprise Data and Platforms IT group at Intel Corporation, is responsible for the corporate oversight and integration of data management, data governance, data compliance and internal analytics services. In addition, as general manager of enterprise data and platforms IT, he oversees the business platforms that support applications for Intel’s Finance, Human Resources (HR), Supply Chain, and Sales and Marketing organizations. His responsibilities in that role span cross-enterprise IT platform architecture, engineering, databases, middleware, big data, business intelligence and advanced analytics. Before assuming his current role in 2017, Safa served as general manager of IT enterprise solutions, where he was responsible for Finance, HR, and Corporate Services business systems. He also led IT cross-enterprise functions for application architecture, SAP engineering, big data platforms, business intelligence and advanced analytics. An Intel veteran currently based in Arizona, Safa has held multiple automation and IT management positions across the company since joining Intel in 1993. His tenure includes 15 years as a development director for factory automation systems, with responsibility for information systems and services supporting Intel’s technology development and high-volume manufacturing. While in that role, he earned an Intel Achievement Award for developing and deploying die-level cherry-picking capabilities. Safa also previously served as decision support systems manager in the Technology Manufacturing Engineering organization, and as automation program manager at Intel’s Fab 11 fabrication facility in New Mexico. Before coming to Intel, Safa was a software engineer with Advanced Micro Devices Inc. Safa earned bachelor’s and master’s degrees in computer science from Texas State University.