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Why Professionals Prefer Hadoop Databases over Traditional Methods

For any technology business, there’s nothing more important than having a good database system in place.

This helps the business to keep track of things such as competitors and rival behaviours.

They can also keep track of the people visiting their company website, including specific audiences who are interested in buying their products or services and learn about their loyal customer base.

How Does Hadoop Help Companies?

It’s crucial for companies to understand that success and growth only comes if they make the required effort to manage and analyse data effectively for the present and the future.

All this information gathering can help a business in a number different ways, and used strategically it can help a business achieve its goals and fulfil targets far more effectively.

In days gone by, database systems were only designed for the purpose of managing a small amount of structured data.

More specifically, it was designed and created to operate on a single server.

But with changing times and technological developments, it becomes very difficult for a business to operate and function using the same outdated tactics.

The traditional database systems restricted the functioning of the business organisations and this lead to the development of Big Data databases such as Mongo database, H-Base database, Riak database, Redis database, Couch database, Cassandra database and much more.

To solve all the problems and issues of traditional database systems, these databases were created or developed so that businesses can function more efficiently.

Hadoop – A Database or Software Ecosystem?

Many people refer to Hadoop is a type of database system.

However, this is wrong. It is in fact a software ecosystem, as it enables parallel computing architecture.

From a technical perspective, it coordinates various types of NoSQL distributed databases like the H-Base database, for example.

The chief of the Hadoop ecosystem is MapReduce.

It is a computational model that fundamentally catches intensive data processes.

H-Base and Hadoop allows data to easily advance across hundreds of servers without any problems or performance lag.

So understandably, this make the Hadoop database system a real game changer!

It easily supports and backs up the different processing needs and requirements of big data.

While the processing of large amounts of data can take more than 18 to 20 hours to complete when distributed on a centralised relational database system, processing huge amounts of data may only take around 3 to 5 minutes when it is distributed or allocated over a large array of Hadoop servers.

A huge reduction in time and processing resources.

When people speak about big data, what they actually refer to is a large collection of both structured and unstructured data.

It is extremely difficult to process large amounts of data quickly using traditional database systems and software methods.

Managed big data acts as a way to help organisations enhance their business operations, work faster and improve key decision making.

These types of companies do not collect and gathers data from a single source only.

They collect data from a number of different sources such as applications, smartphones, various database servers, emails, mobile devices, and other means.

All this data helps companies increase sales volumes, and more importantly, attract and retain new customers.

Data hardware, procedures, data software, exam software, and people are main elements which make up these database systems.

The system administrators, programmers and end users are the core people.

The set of rules are the procedures, and the physical device is the database hardware.

Features & Benefits of Hadoop

The main features and benefits of Hadoop are as follows:

  1. HDFS: The Hadoop Distributed File System is adapted to work with huge or large scale bandwidth
  2. MapReduce: is a highly set up model for the processing of Big Data.
  3. YARN: is a resource scheduler or assistant for Hadoop resource management
  4. Hadoop Libraries: enables third party programs to work with Hadoop

When companies have big data, they often find it difficult to deal with and manage.

So it only makes sense to have software tools which can help them to manage the data more efficiently.

Modern tools and methods are designed to keep in mind the day-to-day problems companies faces and help them to examine and search large datasets with greater ease.

Usually, when businesses face major problems setting up their databases, they often outsource the work.

They will invariably hire firms which are well established, technically proficient and have the right manpower and materials to handle such demands.

These specialist firms are well experienced in installing, designing and managing large scale databases.

Once they have successfully set up their database, the next thing to do is to populate the tables with all the relevant information and contact details customers, prospects, key contacts and target audiences.

Not only this, but they will also have to feed the names and details of current clients.

Making this effort helps businesses to understand which customers are interested in purchasing products and services offered, what they expect from you in the future and the things which you need to do to provide them with a better service.

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