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In this video tutorial, We will be discussing about the need for Hadoop and we also will bediscussing how Horizontal Scaling architecture is better compared to Vertical scaling andTraditional distributed architecture to store and process the Big Data .

If Big Data is implemented in traditional distributed architecture like DBMS, which is suitable

only for working on structured and semi-structured data (partially) like structured

documents, finances, stock records, personnel files and since the traditional data analysis

softwares are not so equipped to handle Big Data as it may take months to process it.

But, as in today's world, organizations are concentrating more on a framework which will help

to store and process structured, semi structured and unstructured data like 3D models,

location data, photographs, audio video files etc on a single platform which are complex to

process in traditional distributed architecture. Hence, Hadoop is the solution which as the

capability to store and process structured, semi-structured and unstructured data in a

distributed architecture.

We all know that more than petabytes of data are generated every day, from various sources

around the world via social media, search engine, Stock market, transport sectors, banking

sectors, e-commerce and many other resources. Since the flow of data continue to grow and

shows no sign of slowing down, it is almost impossible to run the so-called Big Data on

a single machine.

Moreover, because of several limitations on a single machine where a user cannot add

multiple hardware (like ram, hard disk) to a single system and will be very complex to

maintain the hardware when they are added to a single system. This procedure of adding

multiple hardware to a single system is known as Vertical Scaling.

So, in order to increase the storage capacity and the processing power, the best and suitable

solution to handle Big Data is to store the data in a distributed architecture, where users can

add multiple systems or nodes when there is an increase in data. Since the systems are

connected in a distributed architecture, the performance of the processing data will be very

high compared to those running in a single system (Vertical Scaling). This procedure of

storing and processing data in a distributed architecture is known as Horizontal Scaling.

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For more insight on the concepts of Big Data and Hadoop you can refer to our below blogs

Understanding Big Data

Big Data Terminologies You Must Know

Step-by-Step Guide to Become a Big Data Developer

Thus, we hope this blog has helped you understand Need of Hadoop and Use of Horizontal

Scaling architecture.

Keep visiting our website for more post on Big Data and other technologies.

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