Various reports have pegged Big Data market to be worth around $40 billion in 2016.  . Big Data have clearly three leaders – Cloudera, Horton Works and MapR, of which only Horton Works had its IPO. Its stock is trending at around $10 a share.
Horton Works had revenues worth $46 million reported in 2014 . Looking at the steady increase in their revenues over the years, they might touch $100 million in revenues in the year 2016. Hadoop is open source, meaning that companies can use it for free. So how does Horton Works makes money? One word, support. Hortons Works have more than 800 customers at the moment, providing 24/7 web and telephonic support .
Cloudera, being the first to lead in the big data race, has the advantage of a beginner, meaning more customers. Most companies might be reluctant to shift to one of their competitors. Cloudera have also raised about $1 billion, with a big chunk coming from INTEL. Cloudera had claimed more than $100 million in revenues in 2014 , way ahead of Horton Works, and expected to reach $300 million in 2016. Cloudera revenue model is same as Horton Works, meaning selling support.
MapR is quite different from the above two. They are dedicated to creating proprietary extensions to Hadoop while maintaining the API compatibility, but at the same time, provide extra products and capabilities that compliment Hadoop ecosystem to work better. The strength of MapR is in its propritary products like MapR FS, MapR DB and MapR Streams . MapR FS is a POSIX filesystem that supports distributed, reliable, high performance, scalable and fully read/write filesystem. The Hadoop filesystem HDFS, is nowhere close to MapR FS, and is one of the main reasons, why customers prefer MapR. In 2014, MapR had about 700 paying customers . MapR M5 had a price tag of $4000 per node per year , which means they might be making a lot more than Horton Works or Cloudera.
Even if you take the combined market capitalization of all the above companies, its nowhere close to the entire big data market. They are plenty of other players like Syncsort (expected $75 million in big data revenues in 2013), MarkLogic (expected $96 million in big data revenues in 2013), OperaSolutions (expected $124 million in 2013), Actian (expected $138 million in big data revenues in 2013), Pivotol (expected $300 million in big data revenues in 2013), PWC (expected $312 million in big data revenues in 2013), Accenture (expected $415 million in big data revenues in 2013), Palantir (expected $418 million in big data revenues in 2013), SAS (expected $480 million in big data revenues in 2013), Oracle (expected $491 million in big data revenues in 2013), Teradata (expected $518 million in big data revenues in 2013), SAP (expected $545 million in big data revenues in 2013), Dell (expected $652 million in big data revenues in 2013), HP (expected $869 million in big data revenues in 2013), IBM (expected $1.37 billion in big data revenues in 2013)  .
More and more startups are turning up in big data like DataHero (raised $6.1 million in Series A funding), Tamr, Domo (valued at $2 billion), Arcadia Data, Looker, Kyvos Insights, Confluent (raised $24 million in Series B funding), AtScale and ThoughtSpot (raised $30 million in Series B funding).
The year 2016 might see more companies providing proprietary or open solutions to complement the big data or even the Hadoop ecosystem. The open source nature of Hadoop may make it difficult to earn revenues, but there’s absolutelty no barrier for a new company or startup to enter into the big data race. Big data is definitely going to see a proliferation of players and technologies in 2016!