Open Source “Purity,” Hadoop, and Market Realities

March 9, 2013 by Leave a comment

I don’t often do a pure opinion piece but I feel compelled to weigh in on a queston I’ve been asked several times since EMC released its Pivotal HD recently. The question is whether it is somehow inappropriate, even “evil,” for EMC to enter the market without having “enough” committers to open source Apache projects. More broadly, it’s about whether other people can use, incorporate, add to and profit from Apache Hadoop.

–more–

Filed under Gartner, Hadoop, Open source Tagged with , , , , , , ,

Hadoop 2013 – Part Four: Players

March 8, 2013 by Leave a comment

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.

– more – 

Filed under Data Management, Gartner, Hadoop, Industry trends, Mapreduce, Software infrastructure Tagged with , , , , , , ,

Hadoop 2013 – Part Three: Platforms

February 23, 2013 by Leave a comment

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.

– more –

Filed under Data Management, Gartner, Hadoop, Hardware platforms, Industry trends, Mapreduce, Software infrastructure Tagged with , , , , , , , , , , ,

Hadoop 2013 – Part Two: Projects

February 20, 2013 by Leave a comment

In Part One of this series, I pointed out that how significant attention is being lavished on performance in 2013. In this installment, the topic is projects, which are proliferating precipitously. One of my most frequent client inquiries is “which of these pieces make Hadoop?” As recently as a year ago, the question was pretty simple for most people: MapReduce, HDFS, maybe Sqoop and even Flume, Hive, Pig, HBase, Lucene/Solr, Oozie, Zookeeper. When I published the Gartner piece How to Choose the Right Apache Hadoop Distribution, that was pretty much it.

–more–

Filed under Gartner, Hadoop, Industry trends, Mapreduce, Software infrastructure

Hadoop 2013 – Part One: Performance

February 16, 2013 by Leave a comment

It’s no surprise that we’ve been treated to many year-end lists and predictions for Hadoop (and everything else IT) in 2013. I’ve never been that much of a fan of those exercises, but I’ve been asked so much lately that I’ve succumbed. Herewith, the first of a series of posts on what I see as the 4 Ps of Hsdoop in the year ahead: performance, projects, platforms and players.

– more –

Filed under Gartner, Hadoop, Industry trends, Mapreduce, Software infrastructure Tagged with , , , , , , , ,

Hadoop and DI – A Platform Is Not A Solution

February 10, 2013 by Leave a comment

“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.

- more -

Filed under Data Integration, Data Management, Gartner, Hadoop, Magic Quadrant Tagged with , , , ,

Follow

Get every new post delivered to your Inbox.

Join 110 other followers