STAC Report: kdb+ tick analytics in memory on GCP n1-ultramem-160

Outperformed previous Broadwell EX bare metal solution in 8 of 15 benchmarks

5 September 2018

STAC recently performed the STAC-M3 Shasta suite of benchmarks on a stack consisting of kdb+ 3.5 on a Google Cloud Platform (GCP) n1-ultramem-160 instance containing 160 vCPUs and 3.97TB of DRAM, with data loaded from 4TB of Google SSD Persistent Disk.

STAC-M3 is the set of industry standard enterprise tick-analytics benchmarks for database solutions that manage large time series of market data (tick data). STAC-M3 Shasta is similar to the baseline STAC-M3 Antuco suite except that under Shasta, the stack under test (SUT) may pre-load data into memory, and there is no requirement to clear the filesystem cache between benchmarks. In this test, the entire database was pre-loaded into memory and all database operations were performed on data in memory.

The benchmark specifications deliver dozens of test results, which are presented through a variety of tables and visualizations in this report. Google chose to highlight the following comparisons:

• This GCP solution outperformed a bare metal solution based on Broadwell EX and 6TB DRAM (SUT ID KDB160425) in 8 of the 15 required benchmarks.
• This GCP solution outperformed a bare metal solution based on Ivy Bridge EX and 6TB DRAM (SUT ID KDB140116) in 14 of the 15 required benchmarks.
  • In 5 of these benchmarks, the GCP ultramem-based solution was more than twice the speed of the bare metal solution.

Details are in the STAC Report at the links above. Premium subscribers also have access to the code used in this project and the micro-detailed configuration information for the solution. (To learn about subscription options, please contact us.)