Ingest to Insight Big Data Vendor of the Year 2012 and 2013 Outlook: Finalists - Cloudera, IBM, Opera Solutions

Do you know in your bones that serious big data analytics, not just BI, would truly help improve your company’s business model, processes, or stimulate your research discovery efforts, but don't quite know where to start? You would do well to give Cloudera, IBM, or Opera Solutions a call. All three of these big data vendors possess a plethora of products, services, and partnerships yielding more products and services, industry domain, and/or data science expertise, and in IBM's case even big data IT infrastructure and cloud. Any of these 3 suppliers will help you develop and implement a big data solution of considerable value for your organization, or even your entire industry. Do not, however, expect your big data effort to be inexpensive – even if you stick with Hadoop.

IBM offers more big data product than the other two, which works as both blessing and curse, but most importantly IBM brings a wide set of industry domain specific experts with related service to the big data table. IBM has so much going on in terms of big data, including a vast number of alliances, they barely need to refer to all of this as big data anymore, preferring Smarter Analytics, linking their big data efforts with the "Smarter Planet" branding, and suggesting that they stand apart from the rest of the big data mob. What stands out to me, however, is their case study list, which dwarfs the competition. You want proof points about the power of analytics, whether you like the big data term or not? Click here and you will find 47 reference cases from 2012 alone. Suffice it to say that, en masse, IBM brings more people, product, services and partnerships and external awareness to big data than any other organization on the planet.

Opera Solutions combines the services from a bevy of bright data scientists and big data practitioners with one of the most forward looking analytics product available in the form of Vektor, its signal processing platform. Like IBM, Opera has plenty of big data customer success stories to share. In particular, however, is Mobiuss, my favorite big data application to date: My 15 years in banking and personal familiarity with the previous banking debacle (remember the late 1980s when FSLIC went belly-up?) provide me an experience-based appreciation for Mobiuss, a big data solution that has helped move the infamous mortgage-backed securities (MBS) market. Mobiuss arms potential buyers and sellers with enough big data intelligence to make plausible MBS risk evaluations and thus valuations that has helped break a logjam in MBS. Partnerships unveiled with QlikTech, Oracle, and SAP in 2012 underscore Opera Solutions' pull in the big data space, and while InformationWeek put Opera Solutions on their top big data vendors to watch in 2013, we were already watching and impressed in 2012.

Cloudera is a bit of a different animal than IBM or Opera: They too will help you produce a big data solution, albeit purely Hadoop-based, also with a healthy dollop of consulting services as well as their management software, support, and most-used commercial Hadoop distribution. But what puts them on this short list for the top award is how they have pushed the rest of the industry. If Cloudera sneezes, a dozen handkerchiefs are immediately offered from other vendors. They have set the pace for big data partnerships and are the early stage vendor most under the microscope. They have also rolled the innovation dice by trying to deal with the lack of real-time analytics in native Hadoop/Hive through a brave big bet called the Impala project. Cloudera acts as the bellwether of big data early stage vendors, and seems to be handling that responsibility with an appropriate sense of urgency, and a focus on ensuring that the Cloudera distribution of Hadoop is the leading "OS" for big data.

Winner: IBM has put in more hours than any other single organization, from product development to partnerships to marketing, and particularly with services, to propel and popularize big data among the business and public sector masses. The rest of the big data industry owes much to IBM's big data practices and communications to help lift more big data boats than any other vendor.

Big Data 2013 Outlook: Apps, Platforms, and Productivity for the Second Wave

The service-led big data engagement--and note that all of the finalists above excel at services--will not disappear during 2013. But as buyers' profiles shift from early adopters to early majority, discretionary budgets will become slimmer on average, and risk-taking will diminish. Therefore, think of 2013 as a year of transition for big data: Most true data science believers have already made some kind of investment--in fact they needed little convincing. This second wave of big data buyers, however, want a less purely customized, easier to implement approach. They will look for all-encompassing platforms, productivity tools, and even big data apps with lower apparent costs than services-heavy solutions.

ESG has fresh evidence to support the notion that big data investment during 2013 will be healthy, but not over the top: BI/analytics spending, while favorable, sits in the 3rd tier of initiatives in ESG's new 2013 IT spending intentions research data. 44% of respondents to the question, "Which of the following business initiatives do you believe will have the greatest impact on your organization’s technology spending decisions over the next 12 months?" cited "cost reduction initiatives." Security and business process improvement each came in at 31% (multiple selections were allowed). BI/analytics initiatives fell into a group in the 21-25% range that included compliance, mobile computing, and collaboration.

Given this less hype-driven, more conservative big data buyer, which vendors and types of vendors might benefit during 2013? If you haven't heard of NGDATA and you are interested in consumer intelligence, you should look at their Hadoop-based Lily application. In fact, NGDATA offers several industry-specific applications running on a Hadoop backbone. We believe that the equivalent of packaged apps, or something close to packaged analytical apps, represents the next solution phase for the Hadoop community, and NGDATA is already doing it.

Sticking to mainly Hadoop-based solutions, if you are looking for a wider range platform, albeit not quite an app but aiming to deliver apps rapidly, that delivers "ingest to insight" and all the intervening steps all the way to HTML5 visualization, recently unveiled Platfora looks like one of the best examples on the market. Platfora includes its own in-memory analytics engine, potentially eliminating the need for a 3rd party columnar database. While many other Hadoop-based solutions attempt the same thing as Platfora's end-to-end approach, by arriving later to market - late 2012 - than many of its competitors, Platfora was able to learn from others' oversights and mistakes.

What NGDATA and Platfora must ultimately overcome, however, is the challenge of a nouvelle vendor executing in the go-to-market realm - providing references, demos, landing indirect channel, etc. ParAccel has already proven itself in the big data market, and stands out to ESG as the last remaining independent MPP/analytics integrated solution that has, well, successfully already gone-to-market. In no particular order, Teradata aquired Aster Data, EMC acquired Greenplum, IBM acquired Netezza, and HP acquired Vertica. Other large BI/analytics vendors have or are trying to roll their own platforms - SAP, Oracle, Microsoft, SAS for example. Suffice it to say that there are several deep partnership and acquisition scenarios in 2013 that point towards ParAccel.

Providers like ParAccel, Platfora, and NGData point to a couple of market truths associated with the second wave of big data:

  • Less initial VC investments in big data start-ups - the big data big bird is already flying
  • More terse Series B and Series C requirements for existing big data early stage vendors
  • Deepening partnerships, and at least an initial pass in market consolidation - the need for big data "Barney" alliances will diminish, the need for serious go-to-market and technology alliances grows
  • The second wave will want clear answers on security/privacy, information management and costs
Topics: Data Platforms, Analytics, & AI