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–

 

 

Hortonworks IPO – Why Now?

Last week, many observers were surprised when Hortonworks’ S1 for an initial public offering (IPO) was filed. And there are good reasons to be surprised. Why now? CEO Rob Bearden told VentureWire not long ago that he expected to exit 2014 “at a strong $100 million run rate” in preparation for a 2015 IPO. What changed? Perhaps one answer to that question might be answered by asking another question: for whom?

— for more, see my Gartner blog post

Hadoop Investments Continue: Teradata, HP Jockey For Position

Interest from the leading players continues to drive investment in the Hadoop marketplace. This week Teradata made two acquisitions – Revelytix and Hadapt – that enrich its already sophisticated big data portfolio, while HP made a $50M investment in, and joined the board of, Hortonworks. These moves continue the ongoing effort by leading players. 4 of the top 5 DBMS players (Oracle, Microsoft, IBM, SAP and Teradata) and 3 of the top 7 IT companies (Samsung, Apple, Foxconn, HP, IBM, Hitachi, Microsoft) have now made direct moves into the Hadoop space. Oracle’s recent Big Data Appliance and Big Data SQL, and Microsoft’s HDInsight represent substantial moves to target Hadoop opportunities, and these Teradata and HP moves mean they don’t want to be left behind.

more

 

Hadoop is in the Mind of the Beholder

This post was jointly authored by Merv Adrian (@merv) and Nick Heudecker (@nheudecker) and appears on both of our Gartner blogs.

In the early days of Hadoop (versions up through 1.x), the project consisted of two primary components: HDFS and MapReduce. One thing to store the data in an append-only file model, distributed across an arbitrarily large number of inexpensive nodes with disk and processing power; another to process it, in batch, with a relatively small number of available function calls. And some other stuff called Commons to handle bits of the plumbing. But early adopters demanded more functionality, so the Hadoop footprint grew. The result was an identity crisis that grows progressively more challenging for decisionmakers with almost every new announcement.

–more–

Aspirational Marketing and Enterprise Data Hubs

In the Hadoop community there is a great deal of talk of late about its positioning as an Enterprise Data Hub. My description of this is “aspirational marketing;” it addresses the ambition its advocates have for how Hadoop will be used, when it realizes the vision of capabilities currently in early development. There’s nothing wrong with this, but it does need to be kept in perspective. It’s a long way off.

–more–

AAA is Not Enough Security in the Big Data Era

Talk to security folks, especially network ones, and AAA will likely come up. It stands for authentication, authorization and accounting (sometimes audit). There are even protocols such as Radius (Remote Authentication Dial In User Service, much evolved from its first uses) and Diameter, its significantly expanded (and punnily named) newer cousin, implemented in commercial and open source versions, included in hardware for networks and storage. AAA is and will remain a key foundation of security in the big data era, but as a longtime information management person, I believe it’s time to acknowledge that it’s not enough, and we need a new A – anonymization.

More

Hadoop 2013 – Part Four: Players

The first three posts in this series talked about performance projects and platforms as key themes in what is beginning to feel like a  watershed year for Hadoop. All three are reflected in the surprising emergence of a number of new players on the scene, as well as some new offerings from additional ones, which I’ll cover in another post. Intel, WANdisco, and Data Delivery Networks recently entered the distribution game, making it clear that capitalizing on potential differentiators (real or perceived)  in a hot market is still a powerful magnet. And in a space where much of the IP in the stack is open source, why not go for it? These introductions could all fall into the performance theme as well – they are all driven by innovations intended to improve Hadoop speed.

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Hadoop 2013 – Part Three: Platforms

In the first two posts in this series, I talked about performance and projects as key themes in Hadoop’s watershed year. As it moves squarely into the mainstream, organizations making their first move to experiment will have to make a choice of platform. And – arguably for the first time in the early mainstreaming of an information technology wave – that choice is about more than who made the box where the software will run, and the spinning metal platters the bits will be stored on.There are three options, and choosing among them will have dramatically different implications on the budget, on the available capabilities, and on the fortunes of some vendors seeking to carve out a place in the IT landscape with their offerings.

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Hadoop and DI – A Platform Is Not A Solution

“Hadoop people” and “RDBMS people” – including some DBAs who have contacted me recently –  clearly have different ideas about what Data Integration is. And both may  differ from what Ted Friedman and I were talking about in our Gartner research note Hadoop Is Not a Data Integration Solution , although I think the DBAs’ concept is far closer to ours.

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