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Big Data and Hadoop: Will Hadoop Continue to Dominate?
When people talk Big Data today, often they’re talking about Hadoop, a technology first created by Doug Cutting in 2005. Forrester Research says that “Hadoop is unstoppable as its open source roots grow wildly and deeply into enterprises.”
The following are just some of the vendors have built solutions around Hadoop: Amazon Web Services (AWS), Cloudera, Hortonworks, IBM, Intel, MapR Technologies, Microsoft, Pivotal Software, and Teradata.
Analysts like Allied Market Research estimate that the Hadoop market will grow from $2.0 billion in 2013 to $50 billion in 2020. The forecast includes software, hardware and services. Today services represent about half of the Hadoop market. But how realistic are estimates for a product market-size five-years out?
Forrester ticks off the following four reasons as to why Hadoop is so hot today:
- Provides lower cost storage
- Based on open source innovation
- Scales well
- Provides businesses a way to squeeze profits from their data
Allied Market Research attributes the growth in Hadoop to a strong interest in managing structured and unstructured data and big data analytics.
But Hadoop is a platform and forecasts about how Hadoop will grow don’t or can’t factor in the appearance of new competing technologies. Estimates for how technologies will play out six years hence are very difficult to predict. Consider the effect of the iPad and the fact that the first iPad was sold less than five years ago. Things can change quickly. When Big Data is considered as an umbrella category of technologies, it is almost certain to see huge growth between now and 2020, but whether Hadoop will continue to be the center of Big Data in 2020 is less clear.
James Kobelius, IBM Big Data evangelist, says that “Hadoop’s footprint will continue to grow for some time in the big data arena, especially as the core open-source technologies evolve and enterprises invest more heavily in the technology. However, Hadoop will be neither the dominant platform nor the architectural centerpiece of most enterprise big data deployments. But that also applies to any other big data platforms, current or emerging, that you might name.”
