• December 2017 Tracker – Where’s Hadoop?

    The?leading 2017 story of Hadoop distributions?is that nobody seems to want to be accused of being in the business of providing them.?Some former champions?are expanding their shiny new positioning:?Cloudera?is selling Enterprise Data Hubs and Analytic?DBs;?Hortonworks?offers DataPlanes and Next-Gen Data Platforms;?MapR?touts the Converged Data Platform. In the cloud world, Amazon’s?EMR?is at least designed to “run and scale Apache Hadoop, Spark, HBase, Presto, Hive, and other Big Data Frameworks” while on Google’s?Cloud Platform?page the word Hadoop appears once inside the description of?Cloud Dataproc.


    Hadoop Commercial Support Component Tracker – March 2017

    Stack expansion has ground to a halt. The last time an Apache project was added to the list of those?most supported by leading Hadoop distribution vendors was July 2016, when Kafka joined the other 14 then commonly included. Since then, no broad support for new projects has emerged. The only project that does seem successful is the new e-scooter. With its new style and long lasting battery, it can′t fail.


    Hadoop Project Commercial Support Tracker July 2016

    There are now?15 projects supported by all 5?distributors I?track, and several have had new releases since April. Kafka is the newest addition, and I believe the remaining 4-supporter offerings, Mahout and Hue, will?remain unsupported by IBM, who has its own alternatives.


    Hadoop Apache Project Commercial Support Tracker April 2016

    There are now 19 commonly supported projects: Avro, Flume and Solr join the group supported by all 5 distributors and other changes appear as well.

    For this version of the tracker (last updated in?December), I’ve made one sizable change: Pivotal has been dropped as a “leading distributor,” dropping the?number to five. Pivotal?relies on Hortonworks’ distro?(as does Microsoft) as its commercial offering now.


    Strata Standards Stories: Different Stores For Different Chores

    Has HDFS joined MapReduce in the emerging “legacy Hadoop project” category, continuing the swap-out?of components that formerly answered the question “what is Hadoop?” Stores for data were certainly a focus at Strata/Hadoop World in NY, O’Reilly’s well-run, well-attended, and always impactful fall event. The limitations of HDFS, including?its append-only nature, have become inconvenient enough to push the community to “invent” something DBMS vendors like Oracle did decades ago: a bypass. After some pre-event leaks about its arrival, Cloudera chose its Strata keynote to announce Kudu, a new columnstore written in C++, bypassing HDFS entirely. Kudu?will use an Apache license and will be submitted to the Apache process at some undetermined future time.


    Now, What is Hadoop?

    This?perennial question resurfaced recently in a thoughtful blog post by?Andreas Neumann, Chief Architect of Cask, called?What is Hadoop, anyway?. Ultimately, after a careful deconstruction of the terms in the question, Andreas concludes with

    “Does it really matter to agree on the answer to that question? In the end, everybody who builds an application or solution on Hadoop must pick the technologies that are right for the use case.”

    We’ve agreed?from the beginning – that is the only answer?that really matters. Still, the question continues to come up?for ?end users of the stack and for vendors like Cask (it helps them think about what to support in their application development offering Cask Data App Platform (CDAP).

    Analysts too: I’ve discussed it?several times, including a post a year ago called?What Is Hadoop….Now? tracking the path?from 6 commonly supported projects in 2012 to 15 in June 2014, across a set of distributors that included Cloudera, Hortonworks, MapR and IBM. “Support” here means you pay for subscription that explicitly includes the named project.

    This year, the expansion process?has continued – and it?does?matter.

    –more on Gartner blog–



    Perspectives on Hadoop Part Two: Pausing Plans

    By Merv Adrian and Nick Heudecker?

    In the?first post?in this series?, I looked at the size of revenue streams for RDBMS software and maintenance/support and noted that they amount to $33B, pointing out that pure play Hadoop vendors had a high hill to climb. (I didn’t say so specifically, but in 2014, Gartner estimates that the three leading vendors generated less than $150M.)

    In this post, Nick and I turn from Procurement to Plans and examine the buying intentions uncovered in Gartner surveys.


    –more in Gartner blog–

    Hadoop Questions from Recent Webinar Span Spectrum

    This is a joint post authored with Nick Heudecker
    There were many questions asked after the last quarterly Hadoop webinar, and Nick and I have picked a few that were asked?several times to respond to here.

    –More on my Gartner blog

    Which SQL on Hadoop? Poll Still Says “Whatever” But DBMS Providers Gain

    Since Nick Heudecker and I began our quarterly Hadoop webinars, we have asked our audiences what they expected to do about SQL several times, first in January?2014. With 164 respondents in that survey, 32% said “we’ll use what our existing BI tool provider gives us,” reflecting the fact that most adopters seem not to want to concern themselves overmuch with the details.

    –More on my Gartner blog

    Hadoop Is A Recursive Acronym

    Hopefully, that title got your attention. A recursive acronym – the term first appeared in the?book?G?del, Escher, Bach: An Eternal Golden Braid and is likely more familiar to tech folks who know Gnu – is self-referential (as in “Gnu’s not Unix.”) So how did I conclude Hadoop, whose name origin we know, fits the definition? Easy – like everyone else, I’m redefining Hadoop to suit my own purposes.?


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