Teradata partners with Hortonworks on Hadoop

FRAMINGHAM — The growing enterprise interest in Big Data analytics is beginning to drive partnerships between vendors of traditional relational database management technologies and purveyors of the open source Apache Hadoop.

The latest example is Teradata, which on Tuesday announced that it will work with Hortonworks to deliver products and services aimed at helping companies build big data analytics environments based on Hadoop. Hortonworks is a Sunnyvale, Calif.-based spin-off from Yahoo that distributes and supports a commercial version of Hadoop.

Under the partnership, Teradata and Hortonworks will roll out jointly engineered products and develop a reference architecture that companies can use to understand the best-use cases for Hadoop, Arun Murthy, co-founder of Hortonworks, said in a blog . The goal will be to try and help enterprises use Hadoop in conjunction with their existing Teradata data and Teradata Aster analytics technologies.

The announcement between Teradata and Hortonworks comes less than a month after Oracle teamed up with Hortonworks rival Cloudera to deliver a new range of big data appliances. Last October, Microsoft said it would work with Hortonworks on an Apache Hadoop implementation for its Windows Server and Windows Azure platforms.

The partnerships are being driven by surging enterprise interest in Hadoop, a technology that allows companies to capture and analyze vast amounts of structured and unstructured data in a more cost-effective manner compared to incumbent database management systems.

The technology was developed by Yahoo and until recently was used almost entirely by large Internet companies. Over the past 18 months or so, though, a growing number of mainstream enterprises have begun exploring the use of Hadoop for social media mining, sentiment analysis, fraud detection and customer churn management.

The trend has been driving a growing demand for better tools and products that can help companies quickly take advantage of Hadoop without having to design and build everything themselves.

A lot of Teradata customers, for instance, are likely pressing the company for big data analytics technologies that are easy to implement and use, said Tony Baer, principal analyst with market research firm Ovum.

Many companies have begun to see real value in capturing, storing and analyzing large volumes of operational and historical data, he said. “But it can get very expensive when you start talking about petabytes of data on a Teradata [RDBMS] platform” he said. “Hadoop is much more inexpensive.”

Hadoop allows companies to gather, store and refine a wide variety of information, which they can then move to another warehouse for analysis, he said. Many companies have also begun running data analytics applications directly on top of their Hadoop environments, he said.

“The big analytics vendors certainly do need to have a Hadoop distribution,” he said. “I think there is an urgency to have a Hadoop strategy.”

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