Key Business Advantages of Hadoop Development
What is Hadoop?
Apache Hadoop is an open source project that brings an innovative way to store the big data and process it. The name Hadoop is derived from a toy elephant and in the real sense, the framework is like a soft toy only when it comes to processing very large data sets effectively and without any trouble. The framework is written in Java for easy processing of the big data stored in large computer clusters.
In today’s scenario, when Web 2.0 companies are focusing more on big data, Hadoop emerges as an important software framework. Even for numerous traditional enterprises, it can be used for storing and managing data and enjoy its advantages.
Major Advantages of Hadoop
- Scalable: This highly scalable framework can allow you to store and process an incredible amount of data with ease and accuracy. It can distribute large datasets across a number of servers at lightning speed. A traditional database system like RDBMS may fail to distribute such a large amount of data through multiple nodes. On the other hand, Hadoop enables businesses to deploy and run applications that may involve thousands of TB data and can distribute them through several servers.
- Cost Effective: In comparison to traditional database systems, Hadoop proves highly cost-effective when it comes to processing an extremely large amount of data. In traditional systems, it often proves expensive to keep the raw data in store after the processing. However, Hadoop allows to keep the raw data and it is available to a business when needed. Its scalable architecture allows you to store the complete raw data sets at an affordable cost. Thus, a business can save dollars when it comes to storing per terabyte of data using Hadoop.
- Fast Hadoop Development is based on a unique storage method, involving distributed file systems. This unique method allows mapping of the data in clusters. At the same time, the data processing tools are often located on the same servers where the data is stored. This makes the task of data processing much faster than the traditional systems. Hadoop may take a few minutes to process even thousands of terabytes of data.
- Flexible: Using Hadoop in a business can easily get access to new data sources. At the same time, it is possible to tap both structural and non-structural data and process them for valuable outputs. Using various data sources, such as social media, email campaigns etc., it is possible to generate business insights that may result in the business growth. Moreover, a business can take the help of Hadoop to meet their various objectives, such as data warehousing, fraud detection and for the analysis of a marketing campaign.
- Reliable: Hadoop is very less prone to failures in comparison to traditional database systems. When it sends data to a particular node, it is also replicated to other nodes that are available in the cluster. Thus, there is hardly any chance of data loss and it makes a robust and reliable platform for distributing data. If there is any failure, the data can be retrieved from any other node. Moreover, its MapR distribution mechanism ensures the real availability of data by replacing the NameNode architecture with the No NameNode design. The architecture can ensure protection in case of both single and multiple types of failures.
Thus, Hadoop is the best framework when it comes to processing a large amount of data in a fast, cost-effective and error-free manner. For any business that intends to store their data and process it to generate the key business and marketing insights, Hadoop can prove the best system in comparison to traditional database systems. For handling a large amount of structured or unstructured data, a business will have to depend on the Hadoop framework only. And one of the biggest advantages of using Hadoop is that it is resilient to failures.
To get the best out of Hadoop development technology, a business must use the services of a dedicated developers to work on the Hadoop project. ValueCoders provides expert remote developers for all kinds Hadoop requirements.