The Hortonworks Blog

VoltDB is a Certified Hortonworks Technology Partner and developers of an in-memory relational DBMS capable of supporting high volume OLTP and real-time analytics with Hortonworks Data Platform. Our guest blogger today is John Piekos, vice president of engineering at VoltDB.

It’s a common phrase here at VoltDB: Streaming Apps are Really Database Apps When You Use a Database that’s Fast Enough.

What does that mean?

We’re seeing a trend: developers are struggling to create interactive, real-time applications on fast streaming data.…

In our series on Data Science and Hadoop, predicting airline delays, we demonstrated how to build predictive models with Apache Hadoop, using existing tools. In part 1, we employed Pig and Python; part 2 explored Spark, ML-Lib and Scala.

Throughout the series, the thesis, theme, topic, and algorithms were similar. That is, we wanted to dismiss the misconception that data scientists – when applying predictive learning algorithms, like Linear Regression, Random Forest or Neural Networks to large datasets – require dramatic changes to the tooling; that they need dedicated clusters; and that existing tools will not suffice.…

On December 18th, 2014, Hortonworks presented the last of 8 Discover HDP 2.2 webinars: Apache HBase with YARN & Slider for Fast NoSQL Access. Justin Sears, Jeff Sposetti and Mahadev Konar hosted the last webinar in the series.

After Justin Sears set the stage for the webinar by explaining the drivers behind Modern Data Architecture (MDA), Jeff Sposetti and Mahadev Konar introduced Apache Ambari and discussed Ambari innovations now included in HDP 2.2:

  • Configuration Enhancements, including Versioning & History
  • Ambari Administration, including Views Framework
  • Ambari Stacks “Stacks Advisor”

Here is the complete recording of the Webinar

Here are the presentation slides.

Our guest blogger is Carole Murphy, director of product marketing for Voltage SecureStorage at Voltage Security, a Hortonworks Certified Technology Partner.

The demand for Hadoop is accelerating, as enterprises move from proof of concept to full production implementations. With the move to modern data architecture, data security and compliance has become a growing concern.

Securing data in Hadoop is a hot topic and the Hadoop community is investing and providing value-added capabilities in security and governance.…

Apache HBase is the online database natively integrated with Hadoop, making HBase the obvious choice for applications that rely on Hadoop’s scale and flexible data processing. With the Hortonworks Data Platform 2.2, HBase High Availability has taken a major step forward, allowing apps on HBase to deliver 99.99% uptime guarantees. This blog takes a look at how HBase High Availability has improved over the past 12 months and how it will improve even more in the future.…

We are living in a hyper connected world. Digitization has lead to massive improvements in human productivity and enabled us to find solutions that would otherwise be simply impossible. Spurring digitization has been a perfect confluence of network, compute and analytics. Thanks to cloud computing, individuals and enterprises of any scale can continuously collect & process data using dynamic compute resources. Advanced scale out analytics has enabled enterprises to derive insight and operationalize them for improved outcomes.…

The Beginning of our Oil and Gas Journey

Hortonworks began working with the Oil & Gas industry in November of 2013 and our involvement accelerated during a very busy 2014 campaign. Our momentum was set against a backdrop early in the year of milestones in drilling and production across unconventional shale plays in North America, along with with a number of acquisitions, mergers, and divestitures that continued to shape the industry landscape.…

Have you ever wondered how to share content infrastructure that transparently synchronizes information with your existing systems? Are you looking for ways to build an open standards-based platform for deep analysis and data monetization? If so, you will want to join our webinar on Wednesday, January 21st, at 10 AM PT.

Our Big Data experts will teach you how to:

  • Leverage 100% of your data, including text, images, audio, video, and many more data types to be automatically consumed and enriched using HP Haven and Hortonworks Data Platform (HDP).
  • Cindy Maike, GM, Insurance at Hortonworks

    Financial services and the insurance industry are projected by many research organizations to benefit significantly from the usage of new information and advanced analytics by blending new data sources. As an industry, insurance depends on data; however, we have always had to struggle with it and now, we have an explosion of new data available.

    The key is to determine what new information is important to your business strategy and what new questions it can provide insights for, and weave that into existing data sources.…

    The Hadoop Distributed File System (HDFS) is the reliable and scalable data storage core of the Hortonworks Data Platform (HDP). In HDP, HDFS and YARN combine to form the distributed operating system for your data platform, providing resource management for diverse workloads and scalable data storage for the next generation of analytical applications.

    In this blog, we’ll describe the key concepts introduced by Heterogeneous Storage in HDFS and how they are utilized to enable key tiered storage scenarios.…

    Last year on December 11th, Hortonworks presented the sixth of 8 Discover HDP 2.2 webinars: Apache HBase with YARN & Slider for Fast NoSQL Access. Justin Sears, Carter Shanklin and Enis Soztutar hosted this 6th webinar in the series.

    After Justin Sears set the stage for the webinar by explaining the drivers behind Modern Data Architecture (MDA), Carter Shanklin and Enis Soztutar introduced Apache HBase and discussed how to use it with Apace Hadoop YARN and Apache Slider for fast NoSQL access to your data.…

    Our SI partner Ingenious Qube worked with a customer who wanted to price auto insurance based on driving behavior insights obtained from sensors on cars using Hortonworks Data Platform. Rajnish Goswami, CEO of Ingenious Qube, describes the customer story below.

    The Situation

    Insurance companies around the world strive to provide lower insurance rates, and auto insurance is no exception to this phenomenon. The automobile insurance companies are devising ways to derive innovative pricing models that will help customers reduce their insurance premiums; however, it requires an understanding of how one drives their vehicle.…

    This guest blog post is from Srikanth Venkat, director of product management at Dataguise, a Hortonworks security partner.

    Plus ça change, plus c’est la même chose As Jean-Baptiste Alphonse Karr noted “The more things change, the more they stay the same.” Often, that’s not what we hear when looking at Hadoop security: people tend to call out how different Hadoop is, and how different its security solutions need to be.…

    With 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. As more data flows into and through a Hadoop cluster to feed these engines, Apache Falcon is a crucial framework for simplifying data management and pipeline processing.

    Falcon enables data architects to automate the movement and processing of datasets for ingest, pipeline, disaster recovery and data retention use cases.…

    We take pride in producing valuable technical blogs and sharing it with a wider audience. Of all the blogs published in 2014 on our website, the following were most popular:

  • Improving Spark for Data Pipelines with Native YARN Integration.

    Gopal Vijayaraghavan and Oleg Zhurakousky demonstrate improved Apache Spark, which with the help of the pluggable execution context.

  • HDP 2.2 A Major Step Forward for Enterprise Hadoop

    Tim Hall outlines six months of innovation and new features across Apache Hadoop and its related projects.