« Back Why Hadoop is Essential for Big Data?

By  |  Big Data Hadoop  |  On 5/11/2018 9:11:33 PM

Students undergoing Big Data Hadoop Training in Mumbai know that Hadoop not only provides distributed storage but also facilitates distributed data processing. When it comes to s to unstructured data like time stamp, user ID, or social media comments, then traditional data processing spreadsheets or relational databases would not generate sufficient insights. For this you need the prowess of Big Data and Hadoop is the framework that allows for valuable big data processing and analytics.

 Here are some reasons why Hadoop is essential for Big Data

1 – Storage

In a typical architecture data is stored in a storage cluster. From here, it is transferred to a compute cluster to carry out the analytics and processing. Traditional storage system do not have the inbuilt capacity to do the processing by themselves. They need to transfer the data to the computer cluster to carry out the data processing. This is a big drawback when it comes to relational databases.

 With Hadoop this is not the case. As a student of Big Data Hadoop training in Mumbai you would know that Hadoop is designed to execute on a cluster of machines. So storage and processing happens on the go. No additional time is needed to transfer the data and hence processing happens in swift time

 2 – Scalability

Hadoop clusters are designed to scale horizontally. So if you are a student of Big Data Hadoop training in Mumbai and expect a very huge batch of data spanning millions of rows of records, then you can simply add nodes and improve its processing prowess. As a result you don’t need to go hunting for expensive hardware integration when the demand on the existing cluster increases.


3 – Data in any shape, any format

It is not necessary to feed in just structured data to Hadoop. For those undergoing Big Data Hadoop training in Mumbai, it is nice to know that it can easily handle unstructured data as well.

 4 – Does both storage and computing

Hadoop can facilitate both – storage of big data and processing of the data. Traditional databases need different clusters for these two distinct function As a result movement of data from one cluster to another takes time and efforts – a totally unwanted point that is eliminated by using Hadoop.

 To sign off

It is evident that taking part in Big Data Hadoop training in Mumbai will help you make a great career move in Big Data analytics. These above mentioned reasons who exactly why this is the case.