# Weka Delivers Record-Breaking Results on 17 STAC-M3 “Tick Analytics” Benchmarks Using HPE Apollo Systems
**Published:** June 2, 2020
**Location:** CAMPBELL, Calif.
> WekaFS on HPE Apollo 2000 Gen10 systems set 17 STAC-M3 records, delivering industry-leading speed and throughput for algorithmic trading and financial analytics.
_WekaFS on the HPE Apollo 2000 Gen10 systems breaks all prior Weka benchmark records from 2019 and set 5 new ones._
[WekaIO](https://www.weka.io)™ (Weka), the innovation leader in high-performance, scalable file storage for data-intensive applications and a silver partner in the Hewlett Packard Enterprise (HPE) Technology Partner Program, today announced record-breaking performance on the STAC-M3™ Benchmark with HPE Apollo 2000 Gen10 systems. The Weka File System (WekaFS™) running on these HPE servers delivered record-breaking performance at scale for the STAC-M3 “Tick Analytics” Benchmarks—setting 12 STAC-M3 world records for mean query-response times and 5 world records for throughput. These results affirm that an integrated storage solution from Weka and HPE is the ideal choice for algorithmic trading and quantitative analysis workloads common in financial services.
The STAC-M3 benchmark specifications are maintained by the STAC Benchmark Council, which consists of over 500 financial institutions and vendor organizations. The Council’s purpose is to discuss technical challenges and solutions in financial services and to develop useful technology benchmark standards for financial organizations. User firms include the largest global banks, brokerage houses, exchanges, hedge funds, proprietary trading shops, and other market participants. The STAC-M3 results were audited by the Securities Technology Analysis Center (STAC®), which facilitates the Council.
Key benchmark result highlights include:
- Outperformed all publicly disclosed results in 11 of 24 mean-response time benchmarks in the STAC-M3 Kanaga suite:
100-user 12-day VWAB: all 5 benchmark years (STAC-M3.β1.100T.YR.VWAB-12D-HO.TIME)50-user 12-day VWAB: benchmark years 4 and 5 (STAC-M3.β1.50T.YR4VWAB-12D-HO.TIME and STAC-M3.β1.50T.YR5VWAB-12D-HO.TIME)Multi-year high bid: all 4 multi-year spans (STAC-M3.β1.1T.YRHIBID.TIME)
- 100-user 12-day VWAB: all 5 benchmark years (STAC-M3.β1.100T.YR.VWAB-12D-HO.TIME)
- 50-user 12-day VWAB: benchmark years 4 and 5 (STAC-M3.β1.50T.YR4VWAB-12D-HO.TIME and STAC-M3.β1.50T.YR5VWAB-12D-HO.TIME)
- Multi-year high bid: all 4 multi-year spans (STAC-M3.β1.1T.YRHIBID.TIME)
- Outperformed all publicly disclosed results in all 5 throughput benchmarks in the STAC-M3 Kanaga suite (STAC-M3.β1.1T.*.BPS)
- Outperformed all publicly disclosed results in the 100-user 12-day VWAB (no overlap) benchmark in the STAC-M3 Antuco suite (STAC-M3.β1.100T.VWAB-12D.NO.TIME)
The system under test (SUT) was a Kx kdb+ 3.6 database system distributed across 14 HPE ProLiant XL170r Gen 10 servers with dual Intel® Xeon® Gold 6134 CPU @3.2GHz and data stored on HPE servers with WekaFS (v3.6.1) software running on 18 HPE ProLiant XL170r Gen 10 servers, each with 4 NVMe SSDs, using Mellanox SB7790 36-port Non-blocking Managed EDR 100Gb/sec InfiniBand switches. The tests were the baseline benchmark suite (Antuco) and the scaling suite (Kanaga), which uses multiple years of simulated stock market data. STAC-M3 Antuco and Kanaga Benchmark Suites are the industry standard for testing solutions that enable high-speed analytics on time series data such as tick database stacks. The SUT performed faster than a solution using NFS-based NAS and 4 database nodes (KDB190430) on 100% of all the Kanaga multi-year benchmarks and faster than a solution with a single server with direct-attached Optane and 3D NAND on 79% of all Kanaga multi-year mean response time benchmarks. The storage system had a combined performance density of up to 113GB/sec available bandwidth to the client nodes, a maximum observed read throughput of 54.7GB/sec*, and 8.8 million 4K IOPS in 10U, with the ability to fully distribute data, metadata, and system services. In addition, the storage system delivered ultra-low latency by leveraging high-speed networks and NVMe-optimized storage.
The Weka software-defined storage solution is validated for deployment in HPE environments—including those with HPE ProLiant DL360 and the HPE Apollo Gen10 System, which is specifically optimized and purpose-built to serve data storage-centric workloads such as big data analytics and software-defined storage. WekaFS software scales to meet the demanding IOPS and throughput requirements for high-performance data processing, delivering an integrated flash-based parallel file system on HPE servers that can significantly accelerate compute-intensive workloads. For customers, the integrated solution accelerates time-to-market by delivering a low-latency, throughput-optimized environment that provides industry-leading performance, scale, and value.
Barbara Murphy will present “WekaFS for Financial Analytics” at Global STAC Live, an online event starting June 2, 2020. Register at [www.STACresearch.com/spring2020](http://www.STACresearch.com/spring2020).
**Additional resources:**
- The full STAC Report™: [STACresearch.com/KDB200401](http://www.STACresearch.com/KDB200401)
- [WekaIO](https://stacresearch.com/wekaio) landing page at STAC: [STACresearch.com/wekaio](http://www.STACresearch.com/wekaio)
- WekaIO [Blog “What is the STAC-M3 Benchmark and Why Should You Care?](https://www.weka.io/blog/what-is-the-stac-m-3-benchmark-and-why-should-you-care)
- [WekaFS with HPE Apollo 2000 Reference Architecture](https://www.weka.io/resources/reference-architectures/hpe-dl360-reference-architecture)
- [WekaFS with HPE DL360 Reference Architecture](https://www.weka.io/resources/reference-architectures/hpe-dl360-reference-architecture)
- [WekaFS for Financial Services use case](https://www.weka.io/resources/solution-briefs/faster-wall-clock-time-for-better-trading)
*54.7GB/sec in Kanaga 5-year high bid throughput benchmark (STAC-M3.β1.1T.5YRHIBID.BPS)
**Supporting quotes:**
**_Bill Mannel, Vice President of Business Operations for HPC and AI and General Manager of Commercial HPC, HPE, a WIN Innovation partner
_**“We are pleased to see that our joint hardware and software engineered solutions are validated with impressive results on the STAC-M3 benchmarks. Our integrated solution, which includes the HPE Apollo 2000 Gen10 systems, delivers highly-accelerated storage capabilities to support high-performance data analytics environments. Our solution accomplishes this while eliminating possible I/O bottlenecks that occur as customers dramatically increase compute horsepower and fabric bandwidth.”
**_Glenn Wright, Systems Architect, Kx Systems
_**“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’s 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.”
**_Amita Potnis, Analyst, IDC
_**“The industry has seen an influx of new technologies that enable I/O-intensive and extreme technical computing workloads inclusive of high-performance data analytics. And there is increasing widespread adoption of flash storage for higher throughput data movement, but in general, new hardware and networking implementations only rise to their full solution potential when there is a corresponding advancement in software. This philosophy holds true for Weka’s integration with HPE hardware as the distributed and parallel file system optimized for NVMe fully maximizes the benefits of the low-latency, high-throughput capabilities of the system.”
**_Barbara Murphy, Vice President of Marketing, WekaIO
_**“Weka has seen a surge in adoption by customers seeking cost-effective alternatives to legacy storage systems to support their HPDA workloads at scale. WekaFS has been proven to deliver performance that is 3x that of local file systems and 10x that of traditional NAS or SAN, and it is the only shared file solution that can scale to hundreds of clients with no performance degradation. WekaIO is a firm believer in the value of benchmark testing as a means to guide and inform development in the industry and frame results in a manner that delivers actionable intelligence to customers. In addition to breaking world records for the STAC-M3 benchmarks, Weka currently holds several top positions for the independent [SPEC SFS 2014](https://www.weka.io/press-releases/wekaio-matrix-cements-storage-leadership-groundbreaking-performance-latency-results-spec-sfs-2014/) benchmark and the #1 position on [VI4IO’s IO-500 List](https://www.weka.io/press-releases/wekaio-places-first-on-io-500-challenge/).
---
**About WEKA**
WEKA is the AI data and memory infrastructure company transforming the economics of agentic AI. Its WEKA® NeuralMesh™ platform unifies high-performance data storage with extended GPU memory, giving enterprises, AI cloud providers, and AI builders a single foundation for training, inference, and agentic workloads. With Augmented Memory Grid™, NeuralMesh extends GPU memory capacity by 1000x, accelerates time to first token by up to 20x, and delivers 10x more concurrent users from the same GPU footprint, proven in production benchmarks. Trusted by 30% of the Fortune 50, WEKA enables organizations to scale AI faster, optimize GPU utilization, and reduce the cost of every token served. Learn more at [www.weka.io](https://www.weka.io/) or connect with us on [LinkedIn](https://www.linkedin.com/company/weka-io/) and [X](https://x.com/weka).
_WEKA and the WEKA logo are registered trademarks, and WEKA NeuralMesh and Augmented Memory Grid are trademarks of WekaIO, Inc. Other trademarks mentioned herein are the property of their respective owners._
**Media Contact:
**WEKA Communications
[pr@weka.io](mailto:pr@weka.io)
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