Table of Contents
1. Hadoop Best Data Handling tool – Overview
The information they say is power but that is if you are able to effectively utilize it. Before I go into the matter at hand, permit me to digress a little. The world today revolves about data. It includes generating, gathering, analyzing and interpreting data. However, when data is refined, it is no longer data as it becomes information. In other words, information is processed data. An e-commerce development company, for example, is able to effectively provide its services by having access to and utilizing substantial information about e-commerce.
Considering the rate of e-commerce development, it will become cumbersome overtime for that size or amount of data to be handled using the manual method of data handling. Even a Magento e-commerce agency that deals with a specific aspect of e-commerce will be quick to acknowledge that manually handling big data. I’m sure you must be wondering and asking yourself “how then can we handle data? Who or what do we entrust with the issue of data handling?” The answer to your question is Hadoop. What is Hadoop?
2. What is Hadoop?
“Hadoop is an open source framework for storing data and running applications on clusters of commodity hardware.”
It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs. These and many other features make Hadoop the best and biggest technology for handling data. If you want answers to “why Hadoop is best for data handling?” Then this article is here to answer your question comprehensively.
3. Why Hadoop is Best?
3.1 Fault Tolerance
It is not a new thing to hear, see or even witness data loss as a result of critical failure occurring during the process of data transfer. There is hardly a system that is beyond the fault of critical failure. Hadoop however, has figured a way to adapt to this fault. It does this by ensuring that when information is sent to an individual node, that same information is equally reproduced to various different nodes in the cluster. This implies that in case of a fault or error, there is a duplicate copy available for use.
3.2 Speed
This is virtually the drive behind every technological advancement and Hadoop does not disappoint in that regard. Hadoop’s unique storage strategy depends on a disseminated document framework that essentially identifies data wherever it is situated on a cluster. The instruments for data preparation are frequently found on similar servers where the data is actually located. Thus bringing about substantially speedy data handling. In case you’re managing large volumes of unstructured data, then worry no more as Hadoop can effectively process terabytes of data in minutes, and petabytes can be processed in hours.
3.3 Flexible
The traditional method of storing data usually demands that you preprocess ut before you can store it. Hadoop however you can store data the way they are whether structured or unstructured and decide what to do with them later. This implies that Hadoop can be used for a wide variety of purposes, such as log preparing, proposal frameworks, information warehousing, marketing campaign analysis and detecting fraud and misrepresentation, etc. This means that organizations can use Hadoop to get important business-oriented knowledge from information sources, such as online networking, email discussions or clickstream information.
3.4 Affordable
Customary relational database management systems are quite expensive so most firms in a bid to cut cost resort to using down-sample data and classify it on certain assumptions and delete the remaining raw data. The result is that when the business priorities change, the entire raw data models are not available as they have been deleted. however, Hadoop is a platform that offers affordable storage solutions. Its open-source framework is free and uses commodity hardware to store large amounts of data.
4. Conclusion
In this article, we have discussed what is Hadoop and why Hadoop is best for data handling. some of the key features like speed, fault tolerance, flexible, affordable and large development community.
5. References
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