Hortonworks announced the general availability of Hortonworks Dataflow (HDF) 3.0, the next generation of its open source data-in-motion platform. HDF enables customers to collect, curate, analyze and act on all data in real-time, across the data center and cloud.
The growth of the Internet of Things brings new paradigm data from mobile devices, wearable technology and sensors which enterprises can use to uncover actionable intelligence in real-time. Gartner estimates that, “By 2020, 70% of organizations will adopt data streaming to enable real-time analytics” and as such, adoption of HDF has accelerated significantly year-over-year. HDF is the industry’s first open source platform upon which enterprises can quickly build streaming applications for real-time analytics.
“To stay competitive in today’s interconnected world, businesses must harness the insights from data everywhere,” said Scott Gnau, chief technology officer at Hortonworks. “Increasingly, this means from point of creation on connected devices and it’s crucial to make decisions as close as possible to the edge device. With HDF 3.0, we are improving our customers’ experience by simplifying how they create and deploy streaming analytics applications to deliver real time analytics.”
HDF 3.0 introduces Streaming Analytics Manager (SAM), allowing application developers, business analysts and administrators the ability to build streaming applications without writing a single line of code therefore greatly simplifying the process and speeding an application’s time to market. With simple drag-and-drop interface, SAM makes it easy to design, develop, test, deploy and maintain streaming applications on HDF.
A new shared repository of schemas allows applications to flexibly interact with each other across multiple streaming engines including Apache Kafka, Apache Storm and Apache NiFi. Customers benefit from end-to-end data governance and increased operational efficiency.
HDF 3.0 will also be newly available for IBM Power Systems to support a broad range of streaming analytics applications on servers designed for data intensive workloads like big data and cognitive analytics. The combination of HDF and Power Systems delivers industry-leading performance and efficiency for streaming analytics and makes it easier to manage data-in-motion workloads.
“IBM is thrilled to expand our collaboration with Hortonworks to help clients accelerate data analytics for cognitive applications,” said Tim Vincent, vice president and IBM Fellow, Cognitive Systems Software. “HDF on Power Systems brings industry-leading system performance to the edge of the data platform to fuel our clients’ competitive advantage.”