When it comes to Big Data implementation, there’s no bigger name around than Hadoop, to the point that many people think that Hadoop is Big Data. For a variety of reasons the Hadoop framework has become the go to system for numerous Big Data options.
When using Big Data, the process isn’t as simple as just downloading Hadoop and then beginning. A quick visit to the Hadoop website will reveal the complex nature of Hadoop and its programs. There are numerous different modules and projects too, like Hadoop YARN, Hive, Pig, Spark as a Service, etc. It takes a lot to create all these systems, and it also takes a lot for companies to properly implement them.
With all the work that goes into them and their importance in the Big Data field, one of the most important questions to be asked is how viable the current open-source situation of Hadoop is? Can it last?
A Look At Open Source vs. Proprietary
With open source Hadoop, companies that provide the Hadoop service don’t make any money from the Hadoop software itself, they only gain monetarily from the services they provide to help companies use Hadoop to its fullest. On the proprietary side, companies build software off the Hadoop framework that is sold for profit, along with additional services.
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