Aster Data and SAS Partner to Advance Analytics for Big Data Volumes

San Carlos, Calif. – November 16, 2009 - Aster Data, a proven leader dedicated to providing the best data processing and management platform for Big Data applications, today announced it has become a SAS Alliance partner. As a Silver-level SAS partner, Aster Data will work with SAS to help companies manage vast and growing data volumes, perform deep data analysis, and benefit from faster business insights. SAS today announced an expansion of their SAS® In-Database Processing initiative, which also provides more information about this partnership.

"As a SAS partner, we will be able to help businesses preserve the statistical integrity of their SAS engines, giving them unprecedented performance increases during analysis of large data sets," said Mayank Bawa, Aster Data's CEO and co-founder. "We believe this is a major step towards further breakthroughs in business analytics. Organizations can now support more data-intensive applications already prevalent across retail, banking, manufacturing, media and entertainment, telco, and government sectors."

"As SAS continues to intensify its in-database efforts, we seek platform partners, like Aster Data, who complement our analytic offerings and can help deliver superior in-database solutions to customers," said Russ Cobb, SAS Vice President of Alliances and Product Marketing. "As a SAS partner, Aster Data will help drive SAS analytics deeper within the database, and enable companies to make better decisions faster."

Today's big data applications consume vast amounts of diverse data, are highly analytics-intensive, and demand massive, but cost-effective, scaling. Fast data analysis on very large data sets is impossible to perform on traditional data management systems as they simply were not built to store and analyze large, diverse data volumes. Aster Data recently announced Version 4.0, the industry’s first Massively Parallel Data-Application Server that, for the first time, allows applications to run inside Aster's massively parallel data warehouse architecture. The combination of Aster Data and SAS will greatly accelerate business analytics and will enable companies to perform sophisticated analysis and process terabytes of data.

Aster Data and SAS jointly presented to audiences at the recent 12th Annual SAS M2009 Data Mining Conference on the future of big data analytics and how the combined capabilities of the two companies provide the foundation for unprecedented correctness and performance during analysis of large datasets.

About Aster Data
Aster Data is a proven leader in big data management and big data analysis for data-driven applications. Aster Data’s nCluster is the first MPP data warehouse architecture that allows applications to be fully embedded within the database engine to enable ultra-fast, deep analysis of massive data sets. Aster Data's unique "applications-within™" approach allows application logic to exist and execute with the data itself. Termed a "Massively Parallel Data-Application Server," Aster Data's solution effectively utilizes Aster Data's patent-pending SQL-MapReduce together with parallelized data processing and applications to address the big data challenge. Companies using Aster Data include Coremetrics, MySpace, Akamai, Full Tilt Poker, and ShareThis. Aster Data is headquartered in San Carlos, California and is backed by Sequoia Capital, JAFCO Ventures, IVP, and Cambrian Ventures, as well as industry visionaries including David Cheriton, Ron Conway, and Rajeev Motwani. For more information please visit http://www.asterdata.com, or call 1.888.Aster.Data.

Aster Data, Aster Data nCluster, the Aster Data logo and Applications-Within™ are registered trademarks of Aster Data. All other brands and trademarks referenced herein are acknowledged to be trademarks or registered trademarks of their respective holders.

Press Contact:
Marlena Fernandez Berkowitz
ZAG Communications for Aster Data Systems
303.408.3155
marlena@zagcommunications.com

The Best Insights Possible
White Paper: A Revolutionary Approach for Advanced Analytics and Big Data Management
Whitepaper: Deriving Deep Insights from Big Datasets
Research Report: MapReduce and the Data Scientist