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Kdb+ was the database component in recent record-breaking results from Weka, a leader in high-performance, scalable file storage for data-intensive applications, in its recent STAC-M3™ Benchmark tests. The tests are designed to mimic real-life queries in calculating measures like post-trade weighted averages, weekly up to yearly high bid prices, theoretical P&L amongst others. The benchmark results included 12 STAC-M3 world records for mean query-response times and 5 world records for throughput.
Developed in 2010 by several of the world’s largest banks and trading firms, the STAC-M3 benchmark tests provide an independent analysis of performance improvements from emerging hardware and software innovations. Running a variety of compute-intensive operations on a large store of market data, the tests measure the end-to-end performance across the full solution stack of database software, servers, and storage.
Shortly after STAC-M3 was developed, kdb+ quickly became the preferred database platform for hardware vendors running the tests because of its unparalleled performance and response times in processing time-series data.
Commenting on the Weka Benchmark tests Glenn Wright, Systems Architect, KX said:
“We first qualified WekaFS to run kdb+ in Amazon Web Services (AWS) EC2, but we have since seen very good storage performance from WekaFS running kdb+ on bare metal. KX customers have come to expect the very best performance from file systems used to store kdb+ historical analytics data. KX is pleased to recognize the excellent performance of the Weka file system supporting kdb+ as represented in this recent STAC-M3 benchmark.”
Kdb+ is the time-series database that powers the KX Streaming Analytics platform for large scale complex analytics on streaming, real-time, and historical data. It is used in capital markets for algorithmic trading, back-testing, surveillance, regulatory reporting, and research environments as well as in other industries for high-speed sensor monitoring, fault detection, predictive analytics, and machine learning
More detail on the results and the system configuration for the Weka benchmark tests can be found in their press release.