Last Updated on by Kumar Raja

When To Use Big Data Hadoop?

The prominence of Big Data Hadoop is constantly growing with time and is quite successful in catalyzing a revolution in the event of data management. Most of the companies across the IT & Corporate domains have been quite successful in reaping the benefits of Hadoop data management applications to their fuller extent. Companies like LinkedIn, Facebook, Alibaba, Amazon, and eBay are among those companies that investing heavily in this innovative technology.

Let’s have a look at the some of the specific use cases of Hadoop

  • Data searching
  • Data analysis
  • Data reporting
  • Large-scale file indexing  & many more

All these high-end data processing tasks can be effectively managed with Hadoop making it the ideal Big Data tool. In this blog post let’s give you a clear idea on when to use Big Data Hadoop?

Know When To Use Big Data:

To Process Real Big Data-

If you are dealing with enormous levels of data (terabytes or petabytes) then the ideal solution for you would be Hadoop.  There are several other data management tools that can handle data but only upto certain levels & usually fails when it comes to handling enormous levels of data.  Also if you are dealing with data that may expand in the future due to the growth in your business then simply work on Hadoop data management applications.

If this is the case, then you need to work on planning carefully on data management practices for a flexible data processing & storing.  Hadoop has got all the needed tools & algorithms for managing your Big Data.

To Store Diverse Data Sets-

Hadoop possess the ability to store any form of data including:

  • Large or small files
  • Plain text files
  • Binary files (images), or even various data formats across the time period.

Hadoop gives you the flexibility which you need to carry out accurate analysis & data processing.

Some Of The Hadoop Functioning Frameworks Are:

Hadoop Common: Gives the common utilities that support the other Hadoop modules.

Hadoop Distributed File System: Provides high throughput to access different applications data.

Hadoop YARN: Framework used for the cluster resource management.

Hadoop MapReduce Used for parallel processing of enormous sets of data.

Interested to learn more on Hadoop? Be a part of Kelly Technologies leading Big Data Hadoop Training In Hyderabad to learn everything in-depth precisely about Hadoop.

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