Aster Data Systems CTO and Co-Founder to Instruct MapReduce Night School Session at TDWI World Conference

October 28, 2008 – Aster Data Systems, a proven innovator in analytic databases for frontline data warehousing, today announced that it is presenting at an upcoming evening education night school session at the Fall TDWI World 2008 Conference.

Session Title: Introduction to MapReduce Transformations

Who: Tasso Argyros, Aster Data Systems CTO, VP of Engineering, and Co-Founder

What: In his session, Tasso will provide perspective on how the data warehousing industry is being transformed by newer technologies like MapReduce, originally a framework invented by Google. This session will focus on how MapReduce, a controversial topic within data warehousing, can be deployed as a powerful tool in relational databases.

When: Night School session - 6 p.m. Wednesday, Nov. 5
Conference - Nov. 2-7

Where: New Orleans Marriott, New Orleans, LA
Aster Data Systems Booth #314

Registration: For additional event information or to attend the conference, visit http://www.tdwi.org/neworleans/sessions2.aspx?session_code=1188.

About Aster Data Systems
Aster Data Systems is a proven innovator in analytic databases for frontline data warehousing – bringing deep insights on massive data analyzed on clusters of commodity hardware. Co-founded in 2005 by three colleagues in the Stanford Computer Science Ph.D. program, the Aster nCluster database provides patent-pending innovations in performance, availability, and in-database analytics. Aster is headquartered in Redwood City, California and is backed by Sequoia Capital, Cambrian Ventures and First-Round Capital. For more information please visit us at http://www.asterdata.com or via phone at 650-232-4400.

Press Contact:
Aster Data Systems: Leah McLean
Voce Communications
415-848-2583
lmclean@vocecomm.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