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30 June 2008 - Gemstone Systems has announced a partnership with HCL Penstock to meet ultra low–latency requirements of financial firms. HCL will leverage GemStone’s GemFire solution for its Enterprise Risk and Compliance product suite. The combined solution will offer a high performance, in-memory distributed operational data infrastructure that supports low latency, high scalability and resiliency along with high throughput data sharing.

GemStone Partners with HCL Penstock

Pramod Gupta, Vice President, Penstock Product Engineering Group of HCL Technologies: “Through our partnership with GemStone, we are now able to provide robustness and speed to our application users looking for trade turn around times of 10 milliseconds or better."

Regulatory compliance issues commonly associated with MiFID and RegNMS, combined with algorithmic trading, routing and competitive clearing and settlement times have resulted in increased demand among financial institutions to manage large data volumes at sub second speeds. HCL solutions use GemFire’s advanced caching, data virtualization and high availability features to help alleviate these data issues encountered by the upstream and downstream applications.

“We needed a platform that could manage complex data scenario’s like streaming, distributed and federated data from sources across large trading institutions,” states Pramod Gupta, Vice President, Penstock Product Engineering Group of HCL Technologies. “Through our partnership with GemStone, we are now able to provide robustness and speed to our application users looking for trade turn around times of 10 milliseconds or better."

“With global deployments of GemFire through the sales of HCL’s Penstock risk and compliance solution, we are able to reach a broader audience and strengthen user engagements in financial services and other verticals,” said Juan Menendez, Senior Vice President of Business Development and Alliances, GemStone Systems. “Our GemFire solution will provide near real-time data access and smart distribution of fast streaming data, critical to systems such as an analytics engine.”

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