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.

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Microsoft Turns the ‘Scope on SaaS

One of the more interesting conversations I had at the Microsoft Worldwide Partners Conference this week concerned an initiative they have launched to help IT understand – and get under control – proliferating ungoverned SaaS applications. Brad Anderson, Corporate VP for Cloud and Mobility, told the 16,000 attendees that enterprises need help.  “We ask them how many SaaS apps they have in their environment and they usually tell us 30-40. We audit with the Cloud App Discovery tool and find , on average, over 300.” And are these managed? One can only imagine…

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What Is Hadoop….Now?

In February 2012, Gartner published How to Choose The Right Apache Hadoop Distribution (available to clients). At the time, the leading distributors were Cloudera, EMC (now Pivotal), Hortonworks (pre-GA), IBM, and MapR. These players all supported six Apache projects: HDFS, MapReduce, Pig, Hive, HBase, and Zookeeper. Things have changed.

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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.

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Data Security for Hadoop – Add-on Choices Proliferating

In my post about the BYOH market last October, I noted that increasing numbers of existing players are connecting their offerings to Apache Hadoop, even as upstarts enter their markets with a singular focus. And last month, I pointed out that Nick Heudecker and I detected a surprising lack of concern about security in a recent Hadoop webinar. Clearly, these two topics have an important intersection – both Hadoop specialists (including distribution vendors) and existing security vendors will need to expand their efforts to drive awareness if they are to capture an opportunity that is clearly going begging today. Security for big data will be a key issue in 2014 and beyond.

 

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Microsoft’s New CEO – What’s Next for Microsoft?

In the most profound change of leadership in Microsoft’s history, Satya Nadella, who was head of the Cloud and Enterprise division,  has taken the helm, succeeding Steve Ballmer. Nadella’s “insider” understanding of Microsoft’s culture and his effectiveness in cross-team communication and collaboration could help him reshape Microsoft for the digital era — which will be key for the company to attain the visionary technical leadership to which it aspires.

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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.

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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.

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BYOH – Hadoop’s a Platform. Get Used To It.

When is a technology offering a platform? Arguably, when people build products assuming it will be there. Or extend their existing products to support it, or add versions designed to run on it. Hadoop is there. The age of Bring Your Own Hadoop (BYOH) is clearly upon us.  Specific support for components such as Pig and Hive vary, as do capabilities and levels of partnership in development, integration and co-marketing. Some vendors are in many categories – for example, Pentaho and IBM at opposite ends of the size spectrum interact with Hadoop in development tools, data integration, BI, and other ways. A few category examples, by no means exhaustive:

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The Appalling Ratio of US CEO/Worker Pay

My colleague Darryl Carlton and I recently discussed the obscene ratio between CEO pay and average worker pay in the US. And this IS about the US – we are supporting an astonishing gap compared to the rest of the world, and high tech vendors like Oracle are not the only ones at the top of the list – Larry Ellison comes in only number 4 on this Bloomberg list, pulling down 1,287 times what an average Oracle worker (not impoverished at nearly $75K per year) collects.

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