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Why Hadoop is needed for Big Data?

In previous article What is Big Data - for beginners we explained the Big Data. In this article we will explain why Hadoop is needed for Big Data.

Hadoop starts where distributed relational databases ends.

If relational databases can solve your problem, then you can use it but with the origin of Big Data, new challenges got introduced which traditional database system couldn't solve fully.


What is Big Data - for Beginners

Let us understand these challenges in more details.

Challenges for traditional Database management system to handle Big Data


Challenge 1:
Big Data has got variety of data means along with structured data which relational databases can handle very well, Big Data also includes unstructured data (text, log, audio, streams, video stream, sensor, GPS data). The traditional databases require the database schema to be created in ADVANCE to define the data how it would look like which makes it harder to handle Big unstructured data.


What is Big Data - for Beginners

Challenge 2:
Big Data is getting generated at very high speed. The traditional databases are not designed to handle database insert/update rates required to support the speed at which Big Data arrives or needs to be analyzed.


What is Big Data - for Beginners

Challenge 3:
Big Data is data in Zettabytes, growing with exponential rate. If the data to be processed is in the degree of Terabytes and petabytes, it is more appropriate to process them in parallel independent tasks and collate the results to give the output. Traditional database approach can't handle this.


What is Big Data - for Beginners

To handle these challenges a new framework came into existence, Hadoop.
Hadoop is a frame work to handle vast volume of structured and unstructured data in a distributed manner.
Thanks to Hadoop - organizations can readily store, extract and analyze data in volumes that would recently been unthinkable.


Hadoop is not a database


What is Big Data - for Beginners

It's very important to know that Hadoop is not replacement of traditional database.

Unlike RDBMS where you can query in real-time, the Hadoop process takes time and doesn't produce immediate results. Hadoop is a computing architecture, not a database.

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