Hadoop: Housing Open-Source Data Storage in the Tech Era

Hadoop is maintained by Apache Software Foundation

Digital assets are stored in form of Big Data. The storage platform is highly benefitting companies across the globe, especially at the time of the pandemic when everyone started working on a remote basis. 

Big data represents the volume of data, both structured and unstructured being gathered in a single source. It inundates a business on a day-to-day basis. The big data is stored across various computers as the amount is very huge. A single computer can't handle to house big data. Big data is used as an asset that helps an organisation to analyse the predictions accurately with the help of Artificial Intelligence (AI). By the keen analyses on data, AI can leverage better decisions and strategic business moves. 

When we talk about big data, what eventually spark in the learning is Hadoop. While big data procures large files and information in an encrypted format, Hadoop plays an opposite role.

What is Hadoop?

Hadoop is an open-source framework used to store data and run 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. Hadoop's are free for anyone to do modifications with few exceptions. It is often used as a support system to do big data operations.

History of Hadoop

In the late 1900s and early 2000s, technology started evolving in the world. World Wide Web was created and used. Other search engines also took their form to help locate relevant information amid the text-based content. Starters like Yahoo and AltaVista emerged as excitement to the tech era. From there the technology has improved to the state today where search engines are delivering millions of pages to people's use. 

Among the evolution was the brainchild of Doug Cutting and Mike Cafarella which came up with an open-source web search engine called Nutch. The company tried to deliver multiple task operation to the World Wide Web. 

Later in 2006, four major companies collaborated to come up with the automating distributed data storage and processing. Cutting joined Yahoo and took with it the Nutch project. The ideas were obstructed from Google regarding the storage system. In 2008, Yahoo released the open-source project Hadoop to its users. However, the framework and ecosystem of technologies are managed and maintained by the non-profit Apache Software Foundation (ASF), a global community software developer and contributor. 

Features and Modules of Hadoop

Hadoop was developed when creative software engineers came up with a source to store and analyse datasets far longer than be stored and accessed on a physical storage device like a hard disk. The reason behind the idea to create such a source is because physical storage devices when physical storage devices became bigger, it takes longer for the component that reads the data from the disk to move to a specified segment. 

Hadoop stands out remarkably for its wide range of features. Some of them are, 

• Ability to store and analyse big data- Hadoop houses millions of data starting from social media content to company files.
• Computing power- Hadoop distributed computing models processes big data fast.
• Fault tolerance- Data and processing stand credible to situations like hardware failure. 
• Flexibility- The data stored in it is decided by the user. Any amount of storage input is accepted by Hadoop.
• Low cost- Hadoop is an open-source framework that functions free of cost. It uses commodity software to store large quantities of data.
• Scalability- The data extension could be done in a system by adding nodes. 

However, Hadoop is made up of four kinds of Modules. Each of them carries a particular task for analysing big data. 

• Distributed File-System- The module allows data to be stored in an easily accessible format across a large number of linked storage devices.
• MapReduce- Provides basic tools for poking around in the data. It reads data from the datasets and puts it into a format suitable for analysis, performing mathematical operations.
• Hadoop Common- It unveils Jana tools needed for user's computer systems to read stored data.
• YARN- This module manages the resources of the system storing the data and runs the analysis. 

Uses of Hadoop

Organizations are quick to adopt Hadoop for its flexibility. For example, a commoner can alter the data on their purpose. The form of collaboration developed between volunteers and commercial users is a key feature of open-source software. There are many popular ways that Hadoop is used.

Long term data storage at low-cost: Generally, big data storages have input from transactional, social media, sensor, machine, scientific, clickstreams. The low-cost usage of Hadoop lets anyone keep large data information in the platform. A critical thing about data is that it can help you anytime. That is why it is considered as an asset and is stored preciously. 

Data analysis like in big data: Since Hadoop is an extended application of big data, the platform can also do analytical algorithms. Analyzing data is where the actual part of data utilisation happens. Hadoop stands as a sandbox to opportunities that provide innovation.

IoT espoused Hadoop: By extending the Internet of Things (IoT) features in Hadoop, the platform gets an insight on what to communicate and when to act. Users can continuously improve the instructions as data is being constantly updated. The data inputs every time is different from the previously defined patterns.