Hortonworks makes available its latest Hortonworks DataFlow (HDF) 3.1

Hortonworks has announced general availability of Hortonworks DataFlow (HDF) 3.1. The launch of HDF 3.1 enhances operations and developer productivity, and delivers stronger integration and interoperability between HDF and Hortonworks Data Platform (HDP). This new version of HDF delivers a single open-source tool set that integrates governance, security and management across the entire data lifecycle from the edge to analytics to real- time decisions.

“As more and more organizations embrace the value of capturing data in motion, they are also devising more ambitious objectives and sophisticated approaches to maximizing the utility of that data and leveraging the insights provided,” said Scott Gnau, Chief Technology Officer, Hortonworks. “This newest release improves ease-of-use and time-to-value by enabling developer productivity while also expanding enterprise interoperability.”

The new HDF 3.1 offers organizations the following enhancements:

· Improved management of data flows to speed up application development and operations: Apache NiFi Registry, a new Apache sub-project, now included within HDF Enterprise Management Services, facilitates the development, management and portability of data flow. Through this, the export and import of data flows allow easy porting and enables smooth migration of data flows from one environment to another. The functionality improves the storage, control, and management of versioned flows, further shortening the software development life cycle and accelerating application deployment to achieve faster time-to-value.

· Increased developer productivity: HDF 3.1 adds new capabilities to improve streaming data operations in Hortonworks Streaming Analytics Manager (SAM). In the new SAM “Test Mode”, developers can experiment in the creation of SAM apps using mock data and create unit tests for SAM Apps integrated into their continuous integration and delivery environments.

In addition, the new SAM Operations Module gives users the ability to easily test, debug, troubleshoot, and monitor the deployed applications, making the operations of a running application as easy as building the application. These efficiencies will allow developers to reallocate their time toward value-generating initiatives in application creation.

· Increased operational efficiencies through automation: The announcement also includes improvements to Apache Ambari and Apache Ranger that automate the processes for managing Apache NiFi resources. Users can now easily add a new NiFi node to an existing cluster without manually updating node information. Improvements to Apache Ranger allow administrators to quickly define group-based policies for NiFi resources. The elimination of repetitive manual process streamlines the operations to achieve optimal efficiency and utilization of people.