Hadoop, unlike traditional relational database systems, can very effectively support the framework of processing and storing of extremely large data set in a holistic distributed computing eco system. So, without a question, hadoop is a highly scalable storage platform. Businesses that require storage and process of highly complex set of data in a centralized environment can effectively rely on the potentiality of hadoop.
The problem with traditional database management system is that it has been extremely prohibitive to scale up operations and maintain huge influx of operational data at a readily affordable cost. On the other hand, hadoop is a great cost effective storage solution for businesses in the need to upgrade space; quickly, simplistically!
Hadoop offers great flexibility for businesses to access new and updated data sets and tap into a wide variety of structured and unstructured data to generate value. This means business can pull up the flexible nature of hadoop to pull up relatively immense number of useful data from seemingly dissimilar sources such as social media and email conversation
Hadoop's storage system is based on a highly scalable and distributed file system that quickly and methodically maps data wherever it is located in cluster/s. The tools that extract data are usually located on the same server where the data located, thereby making it extremely quick and faster data processing. If you are dealing with a large number of data, such as petabytes; you can access it in preferably hours. This sadly would take days and even weeks if the traditional relational data processing tools are used.
Despite the benefits, hadoop is sometimes criticised for a number of reasons. It falls at the risk of security, vulnerability, potential stability issues and some functional limitations. However; if you consider the overall benefits of using hadoop over the traditional relational data processing tools and software; it stands unmatched.
Another advantage we did not mention on the outset is that hadoop is resilient to failure. The data if failed to load, or processed, is always available elsewhere on the server; thereby there is always a backup.
So, for a robust, updated and stable framework of work, that is highly resilient to failure, and extremely scalable and potentially beneficial and cost effective; you can always use hadoop! To learn more about hadoop training, Cloudera Developer training in delhi, please visit the website!
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