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November 17, 2017 | Piet Loubser | Hortonworks Case Study

Building a global data lake for International Banking

November 13, 2017 | Matt Spillar | Hortonworks Case Study

How Nissan is Harnessing Big Data to Provide Value to Customers

November 10, 2017 | Syed Mahmood | Announcements

Certification of IBM Data Science Experience (DSX) on HDP is a Win-Win for Customers

Viewing posts by: John Kreisa« Back to all

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Our business in Europe continues to expand and I’m excited to share this guest blog post from Geoff Cleaves, Business Intelligence Manager at Billy Mobile a new Hortonworks customer based in Barcelona, Spain. This week at Billy Mobile we are migrating our core technology stack onto HDP 2.3 and boy are we looking forward to […]

As YARN drives Hadoop’s emergence as a business-critical data platform, the enterprise requires more stringent data security capabilities. The Apache Ranger delivers a comprehensive approach to security for a Hadoop cluster. It provides a platform for centralized security policy administration across the core enterprise security requirements of authorization, audit and data protection. On June 10th, […]

Last week, the Apache Slider community released Apache Slider 0.80.0. Although there are many new features in Slider 0.80.0, few innovations are particularly notable: Containerized application onboarding Seamless zero-downtime application upgrade Adding co-processors to app packages without reinstallation Simplified application onboarding without any packaging requirement Below are some details about these important features. For the […]

We hosted an Apache Slider Meetup at our Hortonworks Santa Clara office on March 4th, where committers, contributors, and community members interested in the Apache Slider congregated to hear what’s happening. There were two presenters. To set the context for the audience, Steve Loughran, member of technical staff at Hortonworks, delivered an extemporaneous high-level overview […]

Hortonworks Data Platform’s YARN-based architecture enables multiple applications to share a common cluster and data set while ensuring consistent levels of response made possible by a centralized architecture. Hortonworks led the efforts to on-board open source data processing engines, such as Apache Hive, HBase, Accumulo, Spark, Storm and others, on Apache Hadoop YARN. In this […]

On December 4th, Hortonworks presented the fifth of 8 Discover HDP 2.2 webinars: Apache Kafka and Apache Storm for Stream Data Processing. Taylor Goetz, Rajiv Onat, and Justin Sears hosted this 5th webinar in the series. After Justin Sears set the stage for the webinar by explaining the drivers behind Modern Data Architecture (MDA), Rajiv […]

With Apache Hadoop YARN as its architectural center, Apache Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it for batch, interactive and real-time streaming use cases. Apache Storm brings real-time data processing capabilities to help capture […]

It gives me great pleasure to announce that the Apache Hadoop community has released Apache Hadoop 2.6.0 ! In particular, we are excited about three major pieces in this release: heterogeneous storage in HDFS with SSD & Memory tiers, support for long-running services in YARN and rolling upgrades—the ability to upgrade your cluster software and […]

Hortonworks Data Platform Version 2.2 represents yet another major step forward for Hadoop as the foundation of a Modern Data Architecture. This release incorporates the last six months of innovation and includes more than a hundred new features and closes thousands of issues across Apache Hadoop and its related projects. Our approach at Hortonworks is […]

We are excited to announce that Apache Kafka 0.8.1.1 is now available as a technical preview with Hortonworks Data Platform 2.1. Kafka was originally developed at LinkedIn and incubated as an Apache project in 2011. It graduated to a top-level Apache project in October of 2012. Many organizations already use Kafka for their data pipelines, […]