Hortonworks releases DataFlow 3.0 to simplify streaming apps development

data bulk


Hortonworks has announced the next generation of its open source data-in-motion platform called HortonWorks DataFlow 3.0. The new version is designed to help customers collect, curate and analyse the data derived through their streaming apps in an easier manner.

The new Hortonworks DataFlow version comes with a Streaming Analytics Manager (SAM) that enables developers to build streaming applications without even writing any code. SAM has a simple drag-and-drop interface that makes it easy to design, develop, test, deploy and maintain streaming apps.

In addition to the SAM integration, another notable addition to the Hadoop DataFlow is a new shared repository of schemas that allows applications to easily interact with each other on multiple streaming engines. The new version also supports Apache Kafka, Storm and NiFi engines.

“With Hortonworks DataFlow 3.0, we are improving our customers’ experience by simplifying how they create and deploy streaming analytics to deliver real-time analytics,” said Scott Gnau, CTO of Hortonworks, in an official statement.

IBM Power Systems partnership

San Jose, California-based Hortonworks has partnered with IBM Power Systems. The new partnership is strategically developed to add support for streaming analytics applications to data-intensive servers manufactured by IBM.

IBM Fellow and Vice President of Cognitive Systems Software Tim Vincent believes that the tie-up is a step to accelerate data analytics for cognitive apps. “Hortonworks DataFlow on Power Systems brings industry-leading system performance to the edge of the data platform to fuel our clients’ competitive advantage,” he said.

The expansion of Hortonworks DataFlow will help IoT (Internet of Things) projects to effectively collect data from devices and uncover actionable intelligence in a real time. Notably, the platform is the industry’s first open source approach in the world of streaming apps analytics.


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