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Talend Teams with Hortonworks to Help Big Data Projects Deliver in Real Time

Talend_logo_011315Talend, a global big data integration software leader, has strengthened its partnership with Hortonworks® by supporting a preview version of the latest Apache™ Hadoop® extension, Apache Storm, in Talend 5.6. Apache Storm is ideal for ingesting streaming data that is changing rapidly, such as financial transactions, machine-sensor output, and web click-streams, and enabling real-time responses that can have a massive impact on the bottom line.

Hortonworks is dedicated to expanding and empowering the Apache Hadoop ecosystem, accelerating innovation and adoption of 100-percent open source enterprise Hadoop. By embracing the latest Hadoop-related capabilities, Talend 5.6 will enable a broad range of customers to recognize the benefits of Apache Storm,” said John Kreisa, vice president of strategic marketing, Hortonworks.

Talend, a Hortonworks Certified Technology Partner, generates native Hadoop code and runs data transformations directly inside Hadoop, offering an easy-to-use graphical development environment to dramatically improve the efficiency of data job design. With Talend users can quickly load, extract, transform and process large and diverse data sets from disparate systems.

With faster data integration solutions such as Talend 5.6 and Apache Storm, users can run their analytics more quickly for real-time decision-making, helping them achieve competitive advantages that they just weren’t able to do before,” said Ashley Stirrup, chief marketing officer, Talend. “For many businesses such as online retailers and financial services providers, the availability of high quality data that can be immediately acted upon can be the difference between making a sale and losing a customer.”

As well as embracing Storm, Talend 5.6 also incorporates support for Apache Kafka, the fault-tolerant, publish-subscribe messaging system. Kafka can be used in combination with Apache Storm for real-time analysis and rendering of streaming data.

 

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