An Insider’s Guide to Apache Spark is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new computing framework. As one of the most exciting and widely adopted open-source projects, Apache Spark in-memory clusters are driving new opportunities for application development as well as increased intake of IT infrastructure.
With any large corporation comes data sets so large or complex that traditional data processing applications are inadequate. Tony Vaden, VP and Chief Information Officer at ABC Supply, needed to expand his traditional data archiving and find a Big Data management suite that could help ABC Supply take their data offline but still accessible.
This Introduction to SPARK webinar will feature Daniel Gutierrez, Managing Editor of insideBIGDATA.
In the past year, the Apache Spark distributed computing architecture has continued its upward trajectory amongst the big data players. Its growth has been fueled by several innovative differentiators for big data applications, such as MapReduce 2.0 (or YARN), provisions for analytic workflows, and efficient use of memory. Databricks’ recent 2015 Spark industry survey reports that Spark adoption is outpacing Hadoop because of its accelerated access to big data. In support of this new computing architecture.
I recently caught up with Bernd Harzog, CEO of OpsDataStore and former Gartner analyst. OpsDataStore recently launched out of stealth to provide a big data back-end for all IT management data. The interview touches on the recent launch of OpsDataStore, and the urgent need for big data intelligence in IT operations.
In this special guest feature, Josh Rogers, President of Syncsort, discusses what’s next for Hadoop: how companies can – and should – move beyond its storage capabilities, using more computing nodes to increase their processing power, and the growth of industry-focused applications built on the framework.
Peaxy, Inc. announced the availability of version 3.0 of the Hyperfiler software platform. The new version helps enterprises find, manage, store, mine and reuse exponentially growing data assets. New data services in version 3.0 include index and search, enterprise-grade security, and support advanced analytics in Hadoop or Spark.
Using Qubole Data Service (QDS), a big data analytics platform, TubeMogul made data easily accessible to non-engineering groups across the organization and reduced the amount of engineering time necessary to accommodate users and manage clusters. As a result, they began processing twice as much data in half the time.