What is hadoop?

Hadoop is an open source network which allows storing and processing of big data in the distributed environment of clusters of computers, by the use of simpler models of programming. This software is used for distributed and reliable computing. Hadoop is designed for scaling up from a singular server to thousand machines where each one offer storage and local computation at the same time. This open source software allows huge storage of different kinds of data. The network has immense processing power and can handle unlimited concurrent jobs and tasks in a virtual way.

Benefits of Hadoop:

Hadoop has a wide number of benefits for which people are preferring this network on an enormous scale in these days. Hadoop can process and store large quantities of data within a very short period of time. The distributing computing model of Hadoop can process big data very quickly. With the more number of computing nodes being used, you can have more processing power. There is no need to reprocess data before storing it in the databases.This makes it different from the traditional databases.

 Hadoop allows you to store huge number of data according to your needs. You can store unstructured data like images, videos, texts with the use of Hadoop. The best thing about Hadoop is that it provides protection of data and application against hardware failure. Thus once a node is down, jobs are directed in an automated way which ensures that the distributed computation does not fail. It stores different copies of all the data. The open source framework is absolutely free of cost. You can enlarge the system as well with the addition of more number of nodes. With a wide number of benefits, the usage of Hadoop is increasing for large scale data.

Difference of Hadoop from previous techniques:

Hadoop is much faster and has a cheaper database in comparison to the previous techniques. It is not required to structure the data with Hadoop. You can dump data into framework without reformatting the same. On the other hand, in traditional databases, data needs to be structured and schema needs to be defined before the storage of data. Hadoop has a simplified programming model by which users can write and test data much quickly in distributed systems. With Hadoop, distributed programs can be written much quickly. Hadoop can store data in more diverse formats in comparison to the columns and rows of traditional databases.

Hadoop is easier to administer in comparison to other traditional databases. Hadoop can also handle node failure and other job control issues in an invisible way. As a node fail, Hadoop makes sure that the computations are running on other nodes. It also ensures at the same time that the data stored on the failed node are recovered by the other nodes which makes it different from the traditional databases.
Hadoop can analyze and process huge amounts of unstructured and structured data at much lesser prices in comparison to other databases.


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