Relational Database Management Systems ( Rdbms )

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Nowadays, data is being generated by multiple sources around us at an alarming rate, be it sensors, in the form of social media communications or mobile devices. It has become an important part of an organization, Such data is called big data and the insights from big data can help examine trends, understand customer preferences and help the organizations take better decisions which results in better customer service and effective marketing.

Relational Database Management Systems (RDBMS) provides an efficient way for storage and processing of data but have limitations when it comes to handling Big Data.
Apache Hadoop is an open source framework and its helps in the distributed processing of
Big Data. Hadoop works on a distributed model, has a built in fault tolerance and handles scalability very efficiently. It is able to process data of size petabytes with help of its Map
Reduce Programming model and Hadoop distributed File System.

RDMBS even with parallelizing capabilities and sharding the databases do not scale well for large data sets and are also not cost effective. It is challenging for RDBMS to handle the data size which has increased to petabytes and exabytes. The content from social media, text, video, audio, etc is in semi-structured or unstructured format which cannot be handled by RDBMS. Also, big data grows at a very rapid rate, as an example online retailers maintain records of all the customer interactions in the form of what
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