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DDN and Shakti: Record Results on STAC-M3 Benchmark for Financial Trading Applications

Coupled with EXAScaler appliances, combined solution underscores efficiency and performance that finance customers can achieve.

DDN (DataDirect Networks, Inc.) and Shakti Software, provider of the next generation of performance database analytics, announced record breaking STAC-M3 Benchmark results with their integrated solution, which includes Shakti’s data platform running on a single client server combined with SFA200NVX storage appliance.

Shakti’s data platform was created by renowned computer scientist Arthur Whitney, who created the A+ programming language used by Morgan Stanley and founded the data analysis company KX. Shakti, Whitney’s latest database analytics platform has been proven to deliver results faster and more efficiently than previous versions of his software. Coupled with the company‘s EXAScaler appliances, the combined solution underscores the efficiency and performance that finance customers can achieve.

Shakti was built to deliver data efficiency, hardware efficiency and simplicity to financial institutions, and because DDN is synonymous with high performance, efficiency and flexibility, our partnership is a great match,” said Fintan Quill, director, sales engineering, Shakti Software. “Speed needs speed, and these results show the ability of DDN’s appliance to give great query performance, as seen in this test with a single server. With multiple nodes, DDN and shakti will further demonstrate the efficiency of the database.

Peter Nabicht, president, Securities Technology Analysis Center (STAC) said: “We are pleased to welcome Shakti to the elite group of software providers who have authorized public release of audited STAC-M3 Benchmark results. Financial firms on the STAC Benchmark Council designed STAC-M3 to test a representative range of business use cases, and the need for fast and efficient time-series analysis has never been higher.

In Shakti’s debut STAC benchmark, it achieved noteworthy results using a single server for the entire Shakti database workload.

Results from the baseline (Antuco) suite of STAC-M3 benchmark tests run on this shakti 2.0 (1) solution include:

  • Highest storage efficiency (least storage used for the same database size) of any publicly reported solution. (2)

  • NBBO (3) results 1.7x the speed of the best previously published results for a less-demanding version of the benchmark.

Faster results in several mean-response time benchmarks vs. solution involving kdb+ (4), including:

      • 3.7x the speed in the version of Year-High Bid that allows caching (5)

      • 3.3x the speed in NBBO (6) vs. the less-demanding version of the benchmark

These tests demonstrate the ease with which large quantities of market trade and quote data can be shared with shakti 2.0 across an industry standard, low cost, networked EXAscaler unit.

The Shakti platform is interoperable with all server solutions, allowing financial institutions to easily experience the increase in efficiency and performance using existing servers when paired with DDN storage. With the platform, blocks of data are smaller in size – whether in the cloud or on premise – as compared with other software platforms, allowing customers to take advantage of the velocity found with the company’s storage solutions leveraging a simple reference architecture.

DDN storage is built to deliver the utmost in performance and efficiency to meet the most challenging data-intensive applications, and Shakti’s innovative platform is ideal to demonstrate just how much analysis and insight finance customers can achieve with the right infrastructure,” said Dr. James Coomer, SVP, products, DDN. “These STAC results, along with our partnership, underscore the commitment DDN and Shakti have to deliver flexible, scalable and blazingly fast solutions to the financial market.

(1)Stack under Test (SUT) ID SHK211203 (registration required)
(2) STAC-M3.v1.1.STORAGE.EFF
(3) STAC-M3.ß1.1T.NBBO-Q.TIME
(4) SUT ID KDB211014
(5) STAC-M3.ß1.1T.YRHIBID-2.TIME
(6) STAC-M3.ß1.1T.NBBO-Q.TIME

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