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Introducing Hadoop: Backbone of Big Data Technologies

Last updated on Tue 17 Mar 2020



Big-data is amongst the most modern developments in IT today, and Hadoop stands front and heart of in the debate of just how to handle big-data technology. There’s only one problem that cling to going up: lots of people do not seem to understand what it really means when someone says “Hadoop.”

What is Hadoop?

Hadoop is an open source application framework for keeping data and executing applications on collections of service hardware. It offers substantial storage for almost any type of huge processing power, data and the ability to handle almost unlimited simultaneous jobs or tasks.

Why it matters?

Open-source software:  Open source software maintained and is established with a network of designers from around the world. It is free to get, use and subscribe to, though an increasing number of commercial versions of Hadoop have become accessible.

Substantial storage: The Hadoop framework breakdowns big data into sub-blocks that are kept on groups of service hardware.

Framework: In this situation, it means that the whole thing you want to develop and execute software applications is delivered – connections, programs etc.

Processing power: Hadoop simultaneously handles enormous quantities of data using many low-price computers for quick effects.

Benefits of Hadoop in data handling and management:

One of the main reasons that big organizations turn to Hadoop is its ability to process and handle enormous quantities of data – any type of data – speedily. With data volumes and diversities constantly increasing, especially from social media and the Internet Factors, that’s a key consideration. Other benefits include:

Computing power:It is disseminated computing product easily processes big-data. The more processing nodes you utilize, the more processing power you've.

Flexibility:Contrasting customary relational databases, you do not need top reprocess data before keeping it. You determine how to use it and can keep the maximum amount of data while you want. Which includes unstructured data like videos, images and text.

Fault tolerance:Application and Data processing are secured against failure of hardware. If your node fails, jobs are redirected to other nodes to ensure the distributed computing doesn't fail. And it automatically stores multiple copies of all information.

Low cost:The open-source application framework is absolutely free and usages service hardware to store huge amounts of data.

Scalability: It is simple to expand your system by simply adding more nodes. Small administration is needed.

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