Aster Data’s Data-Analytics Server and Analytic Power of SQL-MapReduce Draws New Partners

New analytics partners including Fuzzy Logix, Cobi Systems, Ermas Consulting, and Impetus Technologies further invest in Aster Data’s unique coupling of SQL and MapReduce for advanced analytics

San Carlos, CA – June 22, 2010 – Aster Data, a proven leader dedicated to providing the best data management and data processing platform for big data analytics, today announced four new partners that are working closely with Aster Data’s data-analytics server, nCluster, to simplify development of highly-advanced and interactive analytic applications that process extremely large data volumes.  Aster Data’s solution is a massively parallel database with an integrated analytic engine that leverages the MapReduce framework for large-scale data processing.  By coupling the SQL language with MapReduce, Aster Data brings organizations the power of MapReduce with the familiarity of SQL. These companies, like many others, are building data-driven applications that leverage the ease and power of Aster Data’s SQL-MapReduce framework and Aster Data’s suite of over 30 business analyst-ready analytic packages and over 1000 power-user functions. The Aster Data Analytic Foundation packages and functions were announced yesterday in a separate release.

“Using SQL-MapReduce, developers can write advanced analytics with modern programming languages, such as Java or C, which are easily invoked declaratively via standard SQL,” said Rick van der Lans, Managing Director, R20/Consultancy. “Not having to deal with the ‘how’ of parallelization implies having to write less code and Aster Data’s data-analytics server both automatically and completely parallelizes query execution. This seriously improves developer productivity and makes ultra-fast advanced analytics feasible for the business analyst.”

Aster Data’s delivery of pre-built SQL-MapReduce functions through the industry’s first massively parallel processing data-analytics server has increased the velocity of advanced analytic application development for partners. These partners recognize the ease-of-use and richness of analytics on big data that can be achieved using Aster Data’s patent-pending SQL-MapReduce framework and visual development environment.  Partners using SQL-MapReduce for rich analytics include:

Fuzzy Logix: “Massive parallel processing of large data volumes, where queries and workloads are automatically parallelized with the elegance and ease of SQL-MapReduce, offers our customers a new level of analytics and productivity that is simply unmatched in today’s marketplace,” said Partha Sen, CEO, Fuzzy Logix. “Given this, we are porting our in-database quantitative library DB Lytix™ to the SQL-MapReduce model and Aster Data platform. On the Aster Data platform, DB Lytix™ will include mathematical and statistical methods, data mining algorithms and Monte Carlo simulation techniques. A vast array of enterprises will be able to take advantage of this general purpose in-database analytics library on the Aster Data platform.”

Cobi Systems: “There’s no question that Aster Data’s data-analytics server and SQL-MapReduce offers a powerful, yet easy-to-use framework to build rich, high performance applications on big data sets,” said Amiya Mansingh, Founder and CEO, Cobi Systems. “We have found that analytics that previously took weeks to months of SQL coding can now be built in days with richer analytic power than what is possible with SQL alone.  We are committed to adding applications to Aster Data’s Analytic Foundation to address the big data analytics needs across various industries, in particular, financial services, insurance, manufacturing and retail.”

Ermas Consulting: “Our focus with Aster Data is on bringing our expertise and solutions built in the SAS and R language to the Aster Data platform and running SAS and R applications 100% in-database using Aster Data’s strong parallelization capabilities,” said Soon Tan, CEO, Ermas Consulting. ”The power of SQL-MapReduce and Aster Data’s advanced in-database analytic engine provides a highly-compelling platform for SAS and R applications on massive data scales.”

Impetus Technologies: “Our research and consulting services team focuses on large data management, and has built considerable proven expertise in this area. Coupled with Aster Data’s analytics innovations around SQL and MapReduce, we can deliver richer data-driven applications that can be built in days using Aster Data’s unique analytics capabilities.  SQL-MapReduce brings an extremely powerful approach that enables richer analytics on big data. The Aster Data partnership is an important part of our business moving forward as market demand for big data management and big data analytics accelerates,” said Pankaj Mittal, CTO, Impetus Technologies.

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 “data-analytics 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, comScore, 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, or call 1.888.Aster.Data.

Aster Data, Aster Data nCluster, the Aster 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.