Tervela Forges Partnership with Teradata for Big Data

ACTON, Mass., Aug. 28, 2012 /PRNewswire/ -- Tervela, the leading data fabric solution provider, today announced it is working together with Teradata, the analytic data solutions company, to deliver enhanced solutions for moving and distributing big data. The partnership will help new and existing customers rapidly acquire large volumes of data from distributed data producers, transport and input it to a Teradata data warehouse or Teradata data appliance for business analysis. Initial testing has already been completed. 

"The Big Data phenomenon is changing the nature of data availability. There is a move away from sequential, batch, overnight processing to parallel, continuous, real-time processing," said Barry Thompson, chief technology officer of Tervela. "This integration provides Teradata customers with an ability to perform very high speed and parallel data ingest and scalably distribute big data across multiple warehouses."

According to Gartner, as companies implement more big data solutions, the need to use high-performance message delivery with those systems will grow.* By integrating the Tervela Data Fabric with the Teradata purpose-built platform family, businesses are able to:

Speed Analysis and Decision Support: Acquire and distribute data in real-time, accelerate loading and time to querying and disseminate results globally in real-time.  Performance benchmarks reveal dramatic improvements in throughput, latency, and scalability compared to other software messaging providers.

Reduce costs of data warehouse infrastructure: Simplify data loading, eliminate redundant storage costs, eliminate wasteful data replication and simplify extract, transform and load procedures. This joint solution also facilitates migration and decommissioning of legacy database infrastructures.

"We are seeing demand for high performance data movement in capital markets and other verticals," said Ben Gillis, area vice president, Teradata. "Our customers are demanding faster time-to-query, especially for big data applications, to support an explosion of analytical systems. Tervela's integration to Teradata will help our customers meet the needs of their consumers."

To learn more about the partnership between Tervela and Teradata, and the benefits of real-time big data distribution, please visit http://www.tervela.com/

*Gartner, Inc., Hype Cycle for Big Data, 2012, Anne Lapkin, July 31, 2012. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About Teradata

Teradata Corporation (NYSE: TDC) is the world's leading analytic data solutions company, focused on integrated data warehousing, big data analytics, and business applications. Teradata's innovative products and services deliver data integration and business insight to empower organizations to make the best decisions possible for competitive advantage. Visit teradata.com for details.

About Tervela

Tervela provides a market-leading data fabric solution that radically improves the reliability, performance and cost efficiency of infrastructures that require high speed, no-loss movement of data across complex and demanding business environments such as global trading, telecommunications, cyber security, and new media. Founded in 2004, Tervela is deployed in leading Financial Services companies, including proprietary trading firms IV Capital and Allston Trading; prime brokerages such as GBM; brokers such as Goldman Sachs; and interdealer brokers and exchanges such as ICAP. For more information, please visit www.tervela.com.

Contact:
Erin Simon
[email protected]
+1 646-586-4220

SOURCE Tervela

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