Posts Tagged Big Data Analytics
The Hadoop ecosystem is an eclectic mishmash of start-ups, mid-sized vendors and IT heavyweights with products and services up and down the Big Data stack. Inevitably the ecosystem will consolidate and thin itself out through mergers, acquisitions and – unfortunately for some of these start-ups – bankruptcies.
Consolidation is part of the natural evolution of any given technology market after an initial period of frenzied innovation, and the Big Data market is no exception. I believe we are witnessing the start of this consolidation today. It will take several years to play out, but the first phase of consolidation is manifesting itself in the form of strategic technical partnerships between vendors that play in different segments of the Hadoop market.
After a (very) brief respite, #theCUBE is back on the conference circuit. Starting tomorrow at 10:20am ET, theCUBE is live for two days at the HP Vertica Big Data Conference (#HPBigData2013) in Boston. Unlike some Big Data shows that focus more on vendors, the Vertica show is heavy on customers and real Big Data end-users.
The benefits of Big Data are often spoken of in the future tense. As in, “Big Data will someday provide enterprises of all types critical insights that allow for increased profitability, improved efficiency and other untold riches.”
Same goes for the technology. Hadoop, some say, will be the foundation of data storage and analytics in the enterprise once it’s proven enterprise-ready.
The reality, however, is that Big Data is today – here and now – delivering on its many promises. We at Wikibon have been documenting Big Data in the Real World for the last two years, including publishing a series of vertical-specific research notes highlighting how enterprises in retail, banking, media, utilities and pharma are leveraging Big Data analytics to drive performance.
Our friends at Forbes.com have put together a fantastic new infographic leveraging data from Wikibon’s Big Data Vendor Revenue and Market Forecast, 2012 – 2017 report. It provides a compelling view of the Big Data universe and illustrates the real revenue vendors are deriving from Big Data. They range from the mega-planets (if you’ll go with me on this analogy) IBM, HP and EMC to the smaller but powerful emerging planets like Hortonworks, 10gen and DataStax.
Ok, not the greatest analogy but still a great infographic:
Mobile devices play a dual role in the context of Big Data. Mobile devices – namely traditional mobile phones, smartphones and tablets – are both sources of Big Data and delivery mechanisms for Big Data.
Mobile as Source of Big Data
Tomorrow marks the kickoff of Strata Conference 2013. This year, SiliconANGLE Wikibon is expanding its coverage from two days to three full days of live broadcast from the show floor. Tune into theCUBE at SiliconANGLE.tv all week to catch it all, and log on to strataconf.com/live between 8:45 am and 10:00 am PST Wednesday and Thursday to watch the live keynotes.
We start things off Tuesday morning when we welcome Edd Dumbill, Co-Chair of the Strata Conference, to theCUBE. Edd and hosts Dave Vellante and John Furrier will preview the upcoming action and layout the themes we’ll be covering.
At its annual PASS Summit today, Microsoft announced that it will include in-memory OLTP capabilities in the next version of SQL Server, due out no earlier than 2014. Code-named Project Hekaton, the additional in-memory transactional-support capabilities will compliment Microsoft’s existing in-memory analytics tools, namely Excel PowerPivot and its xVelocity line, as well as its new Hadoop-based platform HDInsight.
The announcement serves to further solidify in-memory data processing as critical element of next generation Big Data architectures. Other well-known enterprise technology vendors, incuding SAP and Oracle, have likewise embraced in-memory processing capabilities, as have lesser-known but emergent players like Aerospike, DataStax and Kognitio.
Update: MapR and Google announced at Google I/O 2012 that MapR’s Hadoop distributions will be available on-demand via the new Google Compute Engine, validating Wikibon’s previous analysis. Pressure remains on Hortonworks, Cloudera, other Big Data vendors to shore up their cloud strategies.
For the company that invented MapReduce, Google didn’t have much of a presence in the commercial Big Data market until just last month (with the public release of BigQuery.) While Yahoo! engineers took Google’s concept and spearheaded the open source Hadoop movement, Google was happy to quietly develop its own Big Data platform for its own internal use.
- 2012 Will Be the Year of Big Data Applications. Thanks to the intense competition between The Big Three distribution vendors, Hadoop developed rapidly in 2011 and is, by most accounts, enterprise-ready (there are always areas for improvement, of course, notably around Hadoop’s single point of failure issue.) This, along with readily available capital, will result in significant innovation from both existing and new start-up Big Data Application vendors now confident that Hadoop is for real. Expect to see new vertical Hadoop-based Big Data Applications for healthcare, retail, financial services and manufacturing in the year ahead, as well as horizontal applications focused on human capital management and enterprise resource planning. Adoption will start slow, but for traditional enterprises, Big Data Applications are the key to realizing impactful business value from Hadoop. 2012 should be a good year on this front.