Redefining the way in which data can be stored and processed, Hadoop has become a household name for businesses across various verticals.
Hadoop is an open-source, Java-based software framework that stores and distributes large sets of data across several servers that operate in parallel to each other. A part of the Apache project, Hadoop is comprised of two parts:
- The storage part, also known as Hadoop Distributed File System (HDFS)
- The processing part, known as MapReduce.
The increased need to analyse, organise and convert big data into meaningful information is what has contributed to the growth of the yellow elephant, Hadoop, globally. Analysts at Technavio predict that the global Hadoop market will witness a CAGR of more than 59% by 2020.
Created by Technavio; Information sourced from dezyre.com
Top 5 Benefits of Hadoop
Highly cost-effective
This is one of the major benefits of Hadoop. Unlike the traditional relational database management systems (RDMS), which turn out to be quite expensive for processing massive volumes of data, Hadoop gives you the most cost-effective storage solution for gigantic data sets. The HDFS makes use of commodity, which is directly attached to storage and shares the cost of the network it runs on with MapReduce. As the cost of the storage usually determines the viability of the system, Hadoop is highly beneficial for big data deployments. With Hadoop, they can easily store and process orders of more data as compared with the traditional SAS and NAS systems.
Great data reliability
Data reliability is one aspect that no organization wants to compromise on. Hadoop provides complete confidence and reliability; in a scenario where data loss happens on a regular basis, HDFS helps you solve the issue. It stores and delivers all data without compromising on any aspect, at the same time keeping costs down. Whether you are a start-up, a government organization, or an internet giant, Hadoop has proved its mettle when it comes to strong data reliability in a variety of production applications at full scale.
Extremely scalable
Traditional relational database management systems / RDMSs fail to process huge amounts of data. Hadoop, on the other hand, has the ability to store and distribute large sets of data across hundreds of servers. This makes Hadoop highly scalable while costing a company very little. The MapReduce programming of Hadoop allows businesses to run applications from several nodes, involving the usage of thousands of terabytes of data.
Simple, fast and flexible
The USP of Hadoop is simple. Because it is written in Java – a language that is quite widespread and can be picked up easily, Hadoop enables developers to handle tasks with ease and process data efficiently. Along with being simple, the Hadoop framework is fast and flexible. For example, Hadoop’s MapReduce takes a few minutes to process terabytes of data and a couple of hours for petabytes of data.
Comprehensive authentication and security
Security is the top priority of every organization. Any unlawful access to multiple petabytes of data is sure to harm business dealings and operations. All businesses are looking for software that makes their work safe, secure and authenticated. When it comes to authentication and security, Hadoop provides an advantage over other software. Its HBase security, along with HDFS and MapReduce, allows only approved users to operate on secured data, thereby securing an entire system from unwanted or illegal access.
