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The Difference Between Big Data Servers And Dedicated Hosting

Cloud computing stands to see massive growth over the following years. According toForbes, the world cloud computing market stands to hit $411 billion by the time 2020 rolls around. Companies that currently have a local server handling their data are now looking at cloud computing options because of its flexibility, adaptability, and security as compared […]

Cloud computing stands to see massive growth over the following years. According toForbes, the world cloud computing market stands to hit $411 billion by the time 2020 rolls around. Companies that currently have a local server handling their data are now looking at cloud computing options because of its flexibility, adaptability, and security as compared to maintaining a server themselves.

The benefits of having a cloud server that deals with their computing necessities far outweighs the need to maintain their own on-premises server. Moving from these offline methods to an online one does call for a change in how the company views data however. This revamping of the view of data comes hand in hand with the adoption of Big Data as an essential driving aspect of the company’s data management system.

Big Data Conceptualized

In a regular offline data system or a system that is located on-premises, data is usually stored as records located within a centralized set of tables as a database. While this works well for regular data, Big Data requires something a bit more robust. Big Data uses storage techniques referred to as NewSQL or NoSQL systems to handle data that is unstructured from multiple different sources. Datamation contends that unstructured data, like that used in Big Data, is data that does not have a defined schema or categorization and thus can be considered as anything outside of a database. While this seems like a vague definition, based on what we understand about Big Data and its storage, this sort of fits what we expect to see.

The reason the data is stored this way is because it makes more sense to how Big Data is used. Analytical processing of big data requires data to be linked in ways that regular databases don’t allow or that are counter-intuitive to their storage structure. As a result, the usual database language of SQL is not useful in this context, being replaced by JSON and XML since they are more suited for use with data that deals with nodes rather than tables. Pulling data from multiple disparate sources gives an algorithm a wider field from which to draw conclusions as well as more data points to incorporate in order to determine if a trend or correlation exists.

Dedicated Storage for Business

Dedicated hosting is nothing new to business. In the traditional sense, a dedicated server is paid for by a company and only hosts the data that that company generates. Business owners get the benefit of a hosting company’s full support in website hosting, as well as extended benefits such as full control of the data held on the server and high performance access to that data. In many cases, a company’s dedicated hosting package depends upon what that company needs in terms of its network demands. Companies can shop around with different providers to see which one offers the best deals in terms of price to guaranteed uptime and included bandwidth.

Dedicated Big Data Storage

From how we understand Big Data, we know that in order for it to be useful, we need to leverage large volumes of it in order to generate insights that can then be applied to other departments within the company. This is pertinent to how we understand Big Data because it comes back to the unstructured data system we were thinking about earlier. According to Datastax Academy, unstructured data (of which Big Data is a type) needs to have the ability to be replicated across multiple large geographic areas. In order to deal with this, Big Data servers use a form of asynchronous ledgering to record data, making the process faster.

Traditional databases that rely on cheap VPS hosting don’t have the ability to record asynchronously and this can lead to bottlenecks in the case of some processing algorithms. When we consider the sheer volume of data being processed in Big Data analysis, a single bottleneck could lead to serious delays in the overall generation time of results.

A Choice to Make

Businesses will have to make the choice as to whether it makes more sense to keep their currently operating storage system or whether they should look into a cloud solution for dealing with their Big Data needs. It’s no secret that Big Data is better suited to a cloud environment, and the benefits of a distributed cloud server over an on-premises one are readily available for anyone who is interested.

However, some companies prefer sticking with the tried and true method of managing data and that’s fine as well. However, as time marches on, more and more options will appear that might lead to companies seeing the innate value of switching over to more flexible cloud storage solutions. Check Math Formulas for Calcualation.

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