Want to know who is making money in Big Data.  Want to know Market Size?  Now a report just released by research firm Wikibon details it all.

Wikibon.org, the leader in big data, cloud, and converged infrastructure research,  just put out the first ever research report on the size of the Big Data market with vendor leaderboard by revenue.  Link here. 

Wikibon’s research and report is the first market sizing of its kind on Big Data and is an opportunity to see a unique set of data.

The Big Data market is on the verge of a rapid growth spurt that will see it top the $50 billion mark worldwide within the next five years, according to a detailed analysis by Wikibon.

Highlights of the Wikibon report:

–  Big data is a $5 billion dollar market today and is expected to top $50 billion by 2017, a 58% compound annual growth rate.

–  IBM leads the market with a 22% share of the market, largely driven by its’ analytics business and professional services.

–  Finally a surprise is that HP Vertica is #1.  Vertica came out ontop  among the pure plays with 32% share of the market.

As of early 2012, the Big Data market stands at just under $5 billion based on related software, hardware and services revenue. Increased interest in and awareness of the power of Big Data and related analytic capabilities to gain competitive advantage and to improve operational efficiencies, coupled with developments in the technologies and services that make Big Data a practical reality, will result in a super-charged CAGR of 58% between now and 2017.

Wikibon believes Big Data is the new definitive source of competitive advantage across all industries. For those organizations that understand and embrace the new reality of Big Data, the possibilities for new innovation, improved agility, and increased profitability are nearly endless.

Details of the Wikibon Report:

Below is Wikibon’s five-year forecast for the Big Data market as a whole:

Figure 1 – Source: Wikibon 2012

Of the current market, Big Data pure-play vendors account for $264 million in Big Data-related revenue. Despite their relatively small percentage of current overall revenue (approximately 5%), Big Data pure-play vendors – such as Vertica, Splunk and Cloudera — are responsible for the vast majority of new innovations and modern approaches to data management and analytics that have emerged over the last several years and made Big Data the hottest sector in IT.

Wikibon considers Big Data pure-plays as those independent hardware, software or services vendors whose Big Data-related revenue accounts for 50% or more of total revenue. This group also consists of three until-recently independent Next Generation Data Warehouse vendors – HP Vertica, Teradata Aster, and EMC Greenplum – who largely continue to operate as autonomous entities and have not, as of yet, had their DNA polluted by their acquirers.

Below is a worldwide revenue breakdown of the top Big Data pure-play vendors as of February 2012.*

Figure 2 – Source: Wikibon 2012

The current Big Data market leaders, by revenue, are IBM, Intel and HP, although Wikibon expects these megavendors to face increased competition from established enterprise suppliers as well as the aforementioned Big Data pure-plays developing Big Data technologies and use cases that are driving the market. It is incumbent upon Hadoop-focused pure-plays, however, to establish a profitable business model for commercializing the open source framework and related software, which to date has been elusive.

Below is a breakdown of current total Big Data revenue by vendor**:

The Big Data market, therefore, includes those technologies, tools and services designed to address these shortcomings. These include:

• Hadoop distributions, software, subprojects and related hardware;
• Next Generation Data Warehouses and related hardware;
• Data integration tools and platforms as applied to Big Data;
• Big Data analytic platforms, applications and data visualization tools;
• Big Data support, training and professional services.

While this is an admittedly broad market definition, most core Big Data technologies and tools share some combination of the following characteristics. Namely, they take advantage of commodity hardware to enable scale-out, parallel processing techniques; employ some level of non-relational and/or columnar data storage capabilities in order to process unstructured and semi-structured data; and apply advanced analytics and data visualization technology to convey insights to end-users.

Below is a breakdown of Big Data revenue by hardware, software, and services.

Figure 4 – Source: Wikibon 2012

Continue reading the report on Wikibon.org — Link 

Link:  http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues