Entries from March 2013 ↓
March 28th, 2013 — Data management
Google pledges patent support for OSS. Basho open sources Riak CS. And more
And that’s the data day, today.
March 26th, 2013 — Data management
As Q1 comes to a close its time to take another look at our NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects. This is the second update since we rebooted the analysis in September 2012 to account for more products and refine our search terms.
A few interesting statistics to pick out: Neo4j has, as predicted, jumped ahead of MarkLogic for sixth place. No other changes of position, but outside the top ten, shown here, Apache Accumulo continues to grow well.
In fact, Apache Accumulo had the fastest rate of growth for the second quarter in succession, just ahead of DynamoDB and OrientDB -once again – followed by Apache Cassandra and MongoDB.
MongoDB’s growth means that it once again extended its lead as the most popular NoSQL database, according to LinkedIn profile mentions. As the chart below illustrates, it now accounts for 46% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample, compared with 45% in December.
March 25th, 2013 — Data management
451 Research will be hosting its annual HCTS EU event in London on April 9/10. The event includes presentations from 451 Research, Uptime Institute and Yankee Group analysts, as well as representatives from vendors and enterprises – such as HCBS, The BBC, Google, Morgan Stanley, Greenpeace, News International, BNP Paribas, and ING.
We also have a guest speaker in Tim Harford author of “The Undercover Economist”.
As if that wasn’t enough, I’ll be presenting the expanded version of my “Big Data and the Cloud: A Perfect Storm?” presentation.
As I previously wrote ahead of presenting the shortened version at Cloud Expo Europe, many people seem to believe that cloud computing and big data have the potential to create a perfect storm of disruption.
However, 451 Research has been tracking the adoption of data management technologies on the cloud – and the lack of it – since relational databases became available on AWS in 2008, and the effect of the confluence of big data and the cloud would perhaps better be described as dead calm, rather than a perfect storm. Other than development and test environments, adoption has been limited.
In my presentation I’ll take a look at the factors that have restricted adoption of databases in the cloud to date – including some exclusive results from our recent database survey – explain why we see the potential for cloud database growth in the coming years, and examine how the strategies of emerging Hadoop- and database-as-a-service providers are evolving to ensure that big data and the cloud combine to fulfil their potential to disruptive the IT landscape as we know it.
For full details of the event, and to register, click here.
March 22nd, 2013 — Data management
MongoDB goes Enterprise. Riak CS goes open source. And more.
And that’s the data day, today.
March 19th, 2013 — Data management
Splunk adds structure. MapR raises $30m. And more.
And that’s the data day, today.
March 19th, 2013 — Data management
On Tuesday March 26th at 10am PT I’ll be taking part in a webinar with NuoDB on the subject of The New Path to Performance. No Sharding!
As part of the webinar I’ll be explaining the various strategies used by enterprises to attempt to achieve scalability of relational databases, why they fail to meet modern distributed processing requirements, and why companies are increasingly open to looking at alternatives to the traditional relational database.
Wiqar Chaudry from NuoDB will also be discussing how to eliminate technical acrobatics, including:
Sharding
Clustering
Performance tuning
Replication
And other kinds of 20th century database tricks.
To register, click http://go.nuodb.com/no-sharding-webinar-register-s.html
March 14th, 2013 — Data management
SAP’s predictive analytics plans. Dell’s Boomi MDM. And more
And that’s the data day, today.
March 11th, 2013 — Data management
Pivotal HD is not Hadoop
Neither is Cloudera’s Distribution, including Apache Hadoop.
Nor the Hortonworks Data Platform.
Nor the MapR Distribution.
Nor IBM’s InfoSphere BigInsights.
Nor the WANdisco Distro.
Nor Intel’s Distribution for Apache Hadoop.
Apache Hadoop is Hadoop. And Hadoop is Apache Hadoop.
I don’t write that to be pedantic, or controversial, but because it is the only logical conclusion you can reach after reading Defining Apache Hadoop from the Apache Hadoop Wiki.
“The key point is that the only products that may be called Apache Hadoop or Hadoop are the official releases by the Apache Hadoop project as managed by that Project Management Committee (PMC)… Products that are derivative works of Apache Hadoop are not Apache Hadoop, and may not call themselves versions of Apache Hadoop, nor Distributions of Apache Hadoop.”
It is with this in mind that one should view the reaction to EMC Greenplum’s recent launch of of Pivotal HD; and in particular this statement from Scott Yara, EMC Greenplum senior Vice President, Products and Co-Founder:
“We’re all in on Hadoop, period.”
What does it mean to be “all in on Hadoop”? Based on a strict reading of Defining Apache Hadoop (a document that demands by its own words to be read strictly), being “all in” on Hadoop means only one thing: being “all in” on Apache Hadoop.
I have no doubt that EMC Greenplum is “all in” on Pivotal HD, but that’s not the same thing at all.
Not a purity debate
There is nothing wrong with offering additional functionality beyond the scope of Apache Hadoop – the licensing terms clearly encourage it.
As my fellow analyst Merv Adrian notes:
“Having some components of your solution stack provided by the open source community is a fact of life and a benefit for all. So are roads, but nobody accuses Fedex or your pizza delivery guy of being evil for using them without contributing some asphalt.”
That is true. However, to continue the analogy, you would expect any company that claimed to be “all in on roads” to be getting involved in laying and maintaining them, rather than just driving on top of them.
Despite what some people may think this isn’t a matter of arguing about which vendor has the most Hadoop committers. It is a matter of defining what users understand Hadoop to be, and what they understand it not to be. It is a matter of drawing a line between Hadoop – Apache Hadoop – and additional, proprietary, functionality beyond the scope of the project.
User preference
Whether users will choose to go with a pure approach to Hadoop-based products and services is another matter. Dan Woods, for one, clearly believes that products like Pivotal HD will drive further mainstream adoption beyond “the limits of open source.”
The idea is that most enterprises don’t care if it meets the Apache definition of Hadoop or not, as long as it works.
While I have no doubt that some companies will be drawn to the additional features and confidence that vendors such as EMC and Intel can provide, I have also spoken to multiple enterprises – including one very large enterprise just last week – for which the preference is to default to open in order to avoid any potential for lock-in and vendor-specific architecture choices.
There are many vendors that do very much care whether what they are adopting meets the Apache definition of Hadoop.
Which of these attitudes will dominate? I’m not going to pretend I know the answer to that question at this point, but our previous coverage of open source adoption suggests that once the door to openness has been unlocked its very hard to force it shut again.
Dan Woods responded to my (sarcastic) comment about this as follows:
I would dispute that players like IBM, HP, and Intel “took Linux over” but in any case it is undeniable that they had a significant role to play – alongside Red Hat, Novell et al, and individual developers – in turning Linux into an enterprise-grade operating system.
The point is though that they did so by engaging with the Linux project, not by launching their own differentiated versions of Linux.
March 8th, 2013 — Data management
Ayasdi emerges. Amazon slashes DynamoDB prices. And more
And that’s the data day, today.
March 5th, 2013 — Data management
SQL and Hadoop: ascloseasthis. Splunk revenue up 64%. and more.
And that’s the data day, today.
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