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The Challenge Facing Cloudera and Hortonworks: Making Big Data Work

The Challenge Facing Cloudera and Hortonworks: Making Big Data Work

If you are a start-up director in 2016, not a week goes by without someone talking to you about unicorns.

It is difficult to imagine the feeling of riding a unicorn. Do you feel the wind of success rush against its skin? Do you fear the arrows and traps of pitiless hunters? Do you feel a special sense of excitement when you get to the end of the rainbow of profits?

I find it easier to imagine the state of mind of the directors of Cloudera, Hortonworks or MapR, who are now the leading Big Data unicorns.

Three years ago, Wikibon talked about Hadoop  to describe the forthcoming war between Hortonworks and Cloudera. Their particular challenge then was to establish themselves as one of the leaders in Hadoop distribution. Their strategic objective then was to keep the traditional software and database players (IBM, Microsoft, Oracle and HP) outside this ecosystem.

Today, in 2016, there are few reliable statistics available on the deployment rates of Hadoop distributions. A Dezire article mentions 53% for Cloudera, 16% for Hortonworks and 11% for MapR. In any case, it seems clear that Cloudera, Hortonworks and MapR share 80% of the market between them. They have therefore bravely succeeded. 

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But now what is next?

It is not necessarily them to battling it out for a few extra percent. Taking a few extra market points away from Hortonworks is not going to make Cloudera the next Oracle!

In the end, the formula is simple:

Underlying the Hadoop distributions war, a diffuse fear is beginning to take hold of the market, like a fine crack. What if Big Data on Hadoop weren't to work that well?

Indeed, many companies have invested heavily in Hadoop clusters.

 



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