Weka Sets 6 Records on STAC-M3 With WekaFS Parallel File System on Amazon EC2

Benchmark results demonstrate Weka’s ability to help financial services institutions migrate tick-analytics workloads to the AWS cloud and outperform on-premises

CAMPBELL, Calif.–(BUSINESS WIRE)–WekaIO™ (Weka), the fastest-growing data platform for artificial intelligence/machine learning (AI/ML), life sciences research, and high-performance computing (HPC), today announced record-breaking performance of its Weka File System (WekaFS™) on Amazon Elastic Compute Cloud (Amazon EC2) according to the STAC-M3™ Benchmark. An independent audit, conducted by Securities Technology Analysis Center (STAC®), showed that the Weka solution broke 6 STAC-M3 records, confirming that the WekaFS POSIX-compliant file system on Amazon Web Services (AWS) is a capable and performant option for enterprises looking to enjoy the elasticity and agility of tick analytics in the cloud. Financial services use cases such as algorithmic trading, quantitative analytics, and back testing can benefit from these results for hybrid and cloud native workflows.

The STAC-M3 benchmark suite is the industry standard for testing solutions that enable high-speed analytics on time-series data, such as tick-by-tick market data (aka “tick analytics” stacks). STAC-M3 specifications were developed by the STAC Benchmark Council, which consists of over 400 financial institutions and 50 vendor organizations. User firms include the largest global banks, brokerage houses, exchanges, hedge funds, proprietary trading shops, and other market participants.

This testing was performed on Amazon EC2 Non-Volatile Memory Express (NVMe) instances using a kdb+ 4.0 database by KX Systems. Testing included the baseline STAC-M3 suite (Antuco) and the scaling suite (Kanaga).

Key result highlights for this solution, with 15 database server nodes and 40 storage nodes, include:

• Outperformed all publicly disclosed results in 3 of the 5 throughput benchmarks in the STAC-M3 Kanaga suite (STAC-M3.β1.1T.{3,4,5}YRHIBID.BPS)
• Outperformed all publicly disclosed results in 3 of 24 mean-response-time benchmarks in the STAC-M3 Kanaga suite
• Versus a kdb+ 4.0 solution running on a 10-node cluster with 60TB of persistent memory (KDB200603), was faster in 16 of 24 Kanaga and 9 of 17 Antuco benchmarks
• Versus a kdb+ 3.6 solution on a parallel file system with 15 database servers accessing all-flash storage appliances (KDB200915), was faster in 20 of 24 Kanaga benchmarks and 4 of 17 Antuco benchmarks
• Versus a kdb+ 3.6 solution involving 9 database servers accessing networked flash storage (KDB200914), was faster in 15 of 17 Antuco benchmarks

To download or view the full STAC report, visit https://www.STACresearch.com/KDB210507.

Financial organizations with their “Cloud-First” strategy want to increasingly leverage public cloud for its elasticity, scalability, and ease of use for quantitative analytics, back testing, and algorithmic trading. However, these workloads are very latency-sensitive and require consistent high performance to reliably execute. WekaFS, with its record-breaking performance on AWS, has proven that a latency-sensitive mixed workload can effectively be run on AWS, while providing the elasticity and scalability on Amazon EC2 instances. With this capability, Quants and FSI professionals can more frequently run more complex models, perform back testing, and do algorithmic trading to derive actionable insight and match machine trading requirements.

Additional resources:

• The full STAC Report
• WekaIO landing page at STAC
• WekaIO Blog: Quants and Algorithmic Traders Derive Fastest Time to Insights and Time to Market with WekaFS on AWS
• WekaIO Blog: What is the STAC-M3 Benchmark and Why Should You Care?
• WekaFS for Financial Services Use Case
• WekaIO Blog: 5 Reasons to Deploy WekaFS for High-velocity Analytics in Financial Services

Supporting quotes:

“Financial firms designed the STAC-M3 benchmark suite to represent a common set of performance-related challenges in financial time-series analytics,” said Peter Nabicht, president of STAC. “Capital markets participants constantly find themselves having to analyze more data in less time, and competition requires them to do so in a cost-effective manner.

“We first qualified WekaFS to run kdb+ on Amazon EC2, and we now see its full potential record-breaking results,” said Glenn Wright, systems architect at KX Systems. “KX Systems’ time-series database kdb+ is used for large scale complex analytics on streaming, real time, and historical data. Kdb+ is used in capital markets for algorithmic trading, backtesting, surveillance, regulatory reporting, and research environments, as well as in other industries where it is used for high-speed sensor monitoring, fault detection, predictive analytics, and machine learning. 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.”

“In the financial services industry, fintech can be a critical differentiator, enabling companies to outperform their competitors and attract new investments,” said Eric Burgener, research vice president, Infrastructure Systems, Platforms and Technologies Group, IDC. “The ability of extremely high-performance parallel file systems like WekaFS can provide a solid foundation for differentiation in this industry, and WekaIO’s latest benchmark results using STAC-M3 show that the vendor can deliver record-breaking performance not only on in-house infrastructure but also in the public cloud using Amazon EC2 NVMe instances.”

“Capital markets around the world need to analyze more data in less time at the best economics,” said Shailesh Manjrekar, head of AI and strategic alliances at WekaIO. “Public cloud environments were not considered suitable for these workloads due to stringent latency and performance requirements. For the very first time Weka, along with its partner KX systems, demonstrated breakthrough results for STAC-M3 benchmarks, in AWS, thus enabling tick analytics in the cloud and for organizations with a “Cloud-First” Strategy. WekaIO now enables Quants to derive the fastest time to insights and time to market, on-premises or in AWS.”

About WekaIO

WekaIO (Weka) is used by eight of the Fortune 50 enterprise organizations to uniquely solve the newest, biggest problems holding back innovation and discovery. Weka solutions are purpose-built to future-ready the accelerated and agile data center. Optimized for NVMe-flash and the hybrid cloud, its advanced architecture handles the most demanding storage challenges in the most data-intensive technical computing environments, delivering truly epic performance at any scale, enabling organizations to maximize the full value of their data center investments. Weka helps the enterprise solve big IT infrastructure problems to accelerate business outcomes and speed productivity. For more information, go to https://www.weka.io

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WekaIO, WekaFS, Weka AI, Weka Innovation Network, Weka Within, Weka AI logo, WIN logo, Weka Within logo, and the WekaIO logo are trademarks of WekaIO, Inc.

“STAC” and all STAC names are trademarks or registered trademarks of the Securities Technology Analysis Center, LLC.

Contacts

JPR Communications

Judy Smith

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