Maxeler Technologies: Dataflow Computing Platform Provider

Oskar Mencer, CEO & CTO
Data, that was once limited to a single store is now spreading at a faster rate across businesses and beyond; the reason being rampant growth in data generation. Its velocity intensifying day by day is drastically leading to data traffic and more network congestion. Juniper Networks addresses this scenario by providing high-performance network infrastructure for effective flow of data across organizations. Partnering with Juniper is a Palo Alto, CA headquartered company, Maxeler Technologies, who provides transformative solutions that ensure easy flow of data at maximal speed and efficiency.

“By combining dataflow computing with a Juniper switch product, we can bring out maximum performance computing inside the network before the traffic hits the first server. This reduces as well as balances the load on any network and datacenter,” says Oskar Mencer, CEO and CTO, Maxeler Technologies. Maxeler’s affiliation with Juniper has helped them to attain minimal latency in dataflow computing for all their clientele.

Maxeler offers dataflow computing solutions and platforms for diverse applications in oil and gas, university research and financial segments. To facilitate the operations in the financial domain, Maxeler provides Exchange Gateways with FIFO guarantee as a customizable platform, which performs all the financial transactions, risk analytics and derivative models for scenario analysis. “Today, Maxeler dataflow computers are used to make financial markets safer, via fair and reliable exchange gateways,” shares Mencer. Apart from providing platforms for financial operations, Maxeler also offers tremendous support to trading organizations for back testing as well as optimization of trading strategies.

Maxeler’s data flow engine's architecture enables complex computations at a very fast rate without compromising on latency. For instance, JP Morgan required a solution to execute all the credit risk operations in the most precise manner.
The bank adopted Maxeler’s financial dataflow computing platform to perform the credit derivatives risk computations. According to the American Finance Technology Association, by leveraging Maxeler’s data flow engines, the client was able to bring down the time from 8 hours to 2 minutes. Maxeler’s immense performance in the market helped them to gain a stable position in the networking segment. “As a firm, we always focus on maximum performance computing, where we squeeze the last drop of performance out of every Watt we burn. Our operations are also gaining momentum across top business locations such as Central London, and Chicago,” suggests Mencer. Moreover, dataflow engines maintain flexibility and respond promptly to changes in market demand and customer feedback to stay competitive among other contenders. “At Imperial College, physicists are using Maxeler’s computers to simulate interacting particles to improve our understanding of the quantum world,” shares Mencer.

By combining dataflow computing with a Juniper switch product, we can bring out maximum performance computing inside the network before the traffic hits the first server

Moving forward, Maxeler is foreseeing a drastic change in the financial segment with the new enforcement of legislation by government around this domain. “We have recently seen increasing demand and significant deliveries of data computing solutions to China. We also want to focus on security and storage solutions using our Dataflow Engines (DFEs),” states Mencer. Maxeler is predicting a great change and business transformation in the upcoming years especially in the financial segment. “We’re excited about deploying systems to safeguard Big Data from within the core of the organization and also provide Security algorithms in the network, and ultimately making the Internet a safer place,” he concludes.

Maxeler Technologies

Mountain View, CA

Oskar Mencer, CEO & CTO

Provider of dataflow computing platforms, solutions, and appliances for finance, networking, as well as high performance computing domains