IBM Ends Hadoop Distribution, Hortonworks Expands Hybrid Open Source

IBM has followed Intel and EMC/Pivotal in abandoning efforts to make a business of Hadoop distributions, and followed Microsoft in making Hortonworks its supplying partner. At the former Hadoop Summit, now called Dataworks (itself a sign of the shift from Hadoop-centric positioning), IBM announced it will discontinue its IBM Open Platform/BigInsights offering, and will instead OEM Hortonworks’ HDP.

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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.

–More–

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.

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Hadoop Projects Supported By Only One Distribution

The Apache Software Foundation has succeeded admirably in becoming a place where new software ideas are developed: today over 350 projects are underway. The challenges for the Hadoop user are twofold: trying to decide which projects might be useful in big data-related cases, and determining which are supported by commercial distributors. In Now, What is Hadoop? And What’s Supported? I list 10 supported by only one: Atlas, Calcite, Crunch, Drill, Falcon, Kite, LLAMA, Lucene, Phoenix and Presto. Let’s look at them a little more.

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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–

Perspectives on Hadoop: Procurement, Plans, and Positioning

I have the privilege of working for the world’s leading information technology research and advisory company, covering information management with a strong focus for the past few years on an emerging software stack called Hadoop. In the early part of 2015, that particular technology is moving from early adopter status to early majority in its marketplace adoption. The discussions and published work around it have been exciting and controversial, so in this post (and a couple to follow) I describe three interlocking research perspectives on Hadoop: procurement (counting real money actually spent); plans (surveys of intentions to invest) and positioning (subjective interpretations of what the first two mean.)

Procurement Perspective: Hadoop is a (Very) Small Market Today

–more on 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

DBMS Legacies are Very Sticky

Donald Feinberg (@Brazingo) & Merv Adrian (@merv)

Every so often, there’s a wave of interest in the “imminent retirement” of one or more legacy database management systems (DBMS). Usually, it’s because someone with very little knowledge of the actual use and distribution of the products becomes enthusiastic about someone’s sales pitch, or an anecdote or two. Sometimes it’s the result of a “replacement” marketing campaign by a competitor. And so far, it’s usually as illusive- and as far off – as the “death of the mainframe”.

Recently, a financial analyst report stated that in 2015, the industry would begin retiring Sybase products (owned now by SAP) and Informix (owned now by IBM). We and our colleagues have since had several inquiries about this and our response is simple: poppycock. DBMS market data, and our thousands of interactions with customers, do not support any of this.

—more on my Gartner blog–