• April 13, 2016 13 Apr'16

    Hadoop market consolidation continues with Pivotal's exit

    Pivotal Software dropped out of the Hadoop distribution business in favor of reselling the Hortonworks version of the big data framework -- and the market consolidation moves may not be over.

  • April 01, 2016 01 Apr'16

    Streaming analytics puts data in motion at Strata + Hadoop 2016

    Moving streams of data is a must in many modern applications. As a result, streaming analytics systems with Spark Streaming, Kafka and other components are coming to the big data forefront.

  • March 31, 2016 31 Mar'16

    Deep machine learning drives Loop AI quest

    Loop AI Labs' Bart Peintner discusses the transformational impact of deep learning technology, artificial intelligence, and how these tech trends will reshape industries.

  • March 31, 2016 31 Mar'16

    Hadoop core components may not be central to big data future

    At Strata + Hadoop World 2016, Hadoop co-creator Doug Cutting said the core of the distributed processing framework is likely to see its position at the center of big data systems diminish.

  • March 25, 2016 25 Mar'16

    Unstructured data is a misnomer

    Nowadays, the term unstructured data pops up everywhere. It owes its popularity for a large part to the success of big data, to successful technologies such as NoSQL and Hadoop, and to formats such ...

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  • March 24, 2016 24 Mar'16

    Strata + Hadoop World 2016: Hadoop and Spark in spotlight

    The Strata + Hadoop World conference focuses on big data management and analytics technologies, in particular the Hadoop distributed processing framework and Spark processing engine.

  • March 16, 2016 16 Mar'16

    Social media startup uses NoSQL Redis Cloud to 'scale to infinity'

    Because of growing data demands, and the need to nimbly scale up and down, a startup social networking platform chose a Redis Labs NoSQL database management system running on AWS.

  • March 02, 2016 02 Mar'16

    Hortonworks Hadoop distribution goes to two release tracks

    Looking to better balance system stability and innovation, Hadoop distribution provider Hortonworks will follow two release 'cadences' for different component sets in its HDP package.

  • February 29, 2016 29 Feb'16

    Apache Spark architecture speeds data jobs, ousts MapReduce

    Its collection of big-data processing features is priming the Apache Spark architecture for wider deployment. One key trait: Spark performance outpaces MapReduce in many Hadoop use cases.

  • February 24, 2016 24 Feb'16

    AtScale Benchmarks Three SQL-on-Hadoop Engines

    Numerous SQL-on-Hadoop engines are available for accessing data stored in HDFS using the familiar SQL language. They all look promising, they all support a rich SQL dialect, but which ones is the ...

  • February 24, 2016 24 Feb'16

    Spark Streaming update to address growing torrent of big data

    Amid the buzz at Spark Summit East 2016 in New York was word that the Spark data processing engine's stream processing architecture will be overhauled in the upcoming version 2.0 of the open source software.

  • February 04, 2016 04 Feb'16

    HR metrics and analytics bring opportunity, concerns

    HR personnel oversee many of the perks that come with a job, such as paychecks and benefits; the elements that most people would rather avoid, such as firings and employee conflicts; and all things in between, such as education and training. Now, ...

  • February 04, 2016 04 Feb'16

    SQL-on-Hadoop platforms open brave new analytics world

    Hadoop has been slowly plodding through the big data jungle, but SQL's integration may put a spring in the elephant's step.

  • February 03, 2016 03 Feb'16

    NoSQL revs up to the tune of the Spark connector

    Attention's been placed on Spark running on Hadoop, but there are Spark connectors for NoSQL that usher in a new class of operational analytics.

  • January 29, 2016 29 Jan'16

    Data quality metrics a governance must, managers say

    Data governance managers who spoke during an online conference said that tracking business-oriented metrics on data quality improvement is a key to success in governance efforts.