Is Hadoop Adoption Really Worth It?

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Many companies dismiss Hadoop as too difficult to use without ever giving it a chance.

Nowadays, many people seem to be misinformed about Hadoop, mainly due to lots of half-truths that are fluttering about in the market. Hadoop is said to be one of the best tools for big data processing and management due to its high effectiveness and capabilities. Knowledge is power, and so the time has come to debunk these myths and analyze the real facts behind them. It’s time for all those businesses to look at the truth, which can be seen in the return on investment (ROI).

In May 2015, Gartner conducted a survey on Hadoop that revealed many surprising results. It has shown that many companies aren’t currently using and don’t plan to use Hadoop, as they think it is extremely difficult to use, or they do not have enough operators who can work with Hadoop. There are many other reasons too. However, not everyone is opposed to it; many people are very hopeful about Hadoop’s future prospects. The choice of whether or not to use Hadoop can be confusing, as many people don’t really understand the truth about Hadoop, so they are unable to distinguish the facts from the fiction.

Facts and Figures Reveal Hadoop’s Contrasting Nature

There are generally two types of companies in the case of Hadoop’s usage. The first is the reluctant type, who is not sure about the use of Hadoop due to various reasons. The second type consists of those companies and businesses which are really confident about using Hadoop, as they believe that it will give them the maximum ROI. To give you more figures to analyze better, a shortened version of the findings of the Gartner survey from May 2015 are given below. The large target audience of the survey mainly consisted of small to medium sized companies and small C-level executives.

  • About 54% of the target audience refused to invest in Hadoop in the future.
  • Only 18% of the target audience stated that they may use Hadoop in the future.
  • About 26% of the target audience has been using or has just started to use Hadoop.
  • Those companies that weren’t using it then and weren’t planning to use it in the future, pointed out its hard-to-understand user interface and lack of skilled personnel to operate it as the main causes.

Merv Adrian, the vice-president at Gartner, has stated that seemingly Hadoop would not be very successful for at least the next two years, as there are a large number of corporations in the world who aren’t using Hadoop at present, and wouldn’t use it for quite some time in the future as well. Also, lack of interest in Hadoop, despite the increasing need of big data management software, suggests that the demand for Hadoop has been sluggish. The reasons for this are:

  • Not enough skill to operate Hadoop is one of the biggest reasons. Hadoop can be said to be used by very few corporations who can manage to use it efficiently. Some extra third-party tools are emerging in the market to simplify the process, but even these cannot make the process simple enough.
  • Hadoop requires new skills to use, and training employees requires both time and money. Also, pre-existing skills or simple logic cannot be used to operate this complex software. Training can be provided, but it is expected that such programs will gain more importance only in two to three years.
  • Many companies think that Hadoop won’t be of much use. They seem to think of Hadoop as more of a problem than a solution. They think that it is overly powerful, but they aren’t going to need that much power. Also, the overall capital needed to adopt Hadoop is much higher than the actual profit earned by it.

The second group of companies are confident about its use in the future. Some companies have even started using Hadoop for maximum efficiency with increasing benefits. The most powerful and influential feature of Hadoop is that it can process large amounts of data in real time with high accuracy, so it can drastically reduce the chances of deceit. These companies can also work more efficiently as they can carefully analyze customer feedback. They could receive this type of data from a large number of Internet-based sources.

What Do These Findings Mean?

Hadoop is considered to be an extremely advanced tool, and people think that advanced means hard to use. To use Hadoop, one has to learn it properly, which requires large investments in the field. Even the third-party tools that are available cannot always make Hadoop easy enough to operate. So, Hadoop needs to be modified so that it becomes more user-friendly as a front-end tool.


The main thing that companies should know is the potential of Hadoop for big data processing in real time. The companies which realize this earn large profits, preventing fraud at the same time. Processing in real time is more useful than processing in batches, as this can also allow you to provide customers with better products according to their feedback. Hadoop is also more suitable for processing important data in real time rather than processing unvarying data types in batches.


The lack of interest towards Hadoop does not mean that it is not useful. It simply means that many companies still don’t know enough about it. As such, these companies have to use Hadoop in a manner that meets their needs for efficiently solving problems. It can be used for data processing in real time, especially conventional data. There are many other features and uses of Hadoop too, but they are yet to be discovered. However, it needs to be tailored and its user interface is desperately in need of a change. It needs to be made simpler so that anyone can use it. So, at this rate of adoption for Hadoop, it is fair to say that it will be suitable for widespread adoption only after a few years.


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Kaushik Pal
Technology writer
Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…