1 A commissioned study conducted by Forrester Consulting, “Emerging Technology Assessment: The Total Economic Impact™ Of Using Both IBM And Red Hat Solutions Together.” June 2019.
2 Based on IBM internal testing running MongoDB’s Geospatial queries at 700 users, each running 1000 transactions using jmeter v4. Each container uses MongoDB 4.0.2 & Node.js v8.14.1 (REST APIs) with socket bound containers. Testing added containers to each server until servers reached response time limit of 99% of transactions completing in under 1 second. Results valid as of 7/16/19. Conducted under laboratory condition with speculative execution controls to mitigate user-to-kernel and user-to-user side-channel attacks on both systems, Individual result can vary based on workload size, use of storage subsystems & other conditions. Details about MongoDB workload: https://docs.mongodb.com/manual/tutorial/geospatial-tutorial/
3.2X greater containers/core is based on 174 containers/20 cores for Power L922 and 98 containers/36 cores for Intel Xeon. – (2,531/20)/(2,290/36) = 3.2
2.6X Better price performance is based on $666/container for Power L922 and $1,762 for Intel Xeon - 1747/666 = 2.6.
IBM Power L922 (2x10-core/typical 2.9 GHz/256 GB memory) 2x 388 GB SSD, 2x 10 Gb two-port network, RHEL 7.6 with PowerVM (2 partitions@10-cores each), Competitive stack: 2-socket Intel Xeon Skylake Gold 6150 (2x18-core/ 2.7 GHz/256 GB memory), 2 x 480 GB SSD, 3 x 10 Gb two-port network, RHEL 7.6, KVM (2 VMs@18-cores each)
Pricing is based on Power L922 https://www.ibm.com/it-infrastructure/power/scale-out, and publically available x86 pricing https://ark.intel.com/content/www/us/en/ark/products/
3ITIC 2020 Global Server Hardware, Server OS Reliability Report, April 2020