Hadoop

How big data servers are different from regular dedicated hosting servers

10th Jul `17, 11:00 AM in Hadoop

The cloud industry is developing at a fast rate in today’s technological world. For business owners, it has…

Evie Harrison
Evie Harrison Contributor
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The cloud industry is developing at a fast rate in today’s technological world. For business owners, it has brought more choices. Everyone wants to gain an edge over their competitors and choose the best technology with the best business intelligence. Naturally, the decision is governed by the kind of IT infrastructure your business requires. Cloud computing has also brought its own set of options for every business. The global public cloud market will top $146 billion in 2017, up from just $87 billion in 2015 and is growing at a 22% compound annual growth rate. Our systems are drowning in data, which needs to be kept secure to maintain normal business functionality.

With ‘Big Data’, the debate moves beyond traditional data handling techniques to a bigger scale. Analysis on this big a scale is possible if your business uses a platform that can deal with this amount of information on a daily basis. Servers that can manage the amount of storage required and process this data based on the desired queries have to be chosen by business owners.

Are you confused about the options regarding hosting your application or website? If you are not sure whether cloud servers or dedicated servers are for you, take a look at these distinguishing factors mentioned below;

Big data concepts are bigger than just data which isn’t made to be handled by regular servers. It is a whole process which includes the collection, handling, processing and storage of data. You should brace yourself for Big data. It’s going to hit your systems if it already hasn’t.

Big data platforms (also referred to as NoSQL or NewSQL databases) deal with unstructured information, which is pulled in from a number of disparate sources, and may exist in various formats. The attributes of each record may vary on an individual basis. Creating and exploring relationships between records often occurs on a case-specific basis, for which laying out the information in tables isn’t appropriate. So standard formats like XML and JSON which cater for variable nodes and node attributes are used, and individual records are stored discretely, with complex algorithms being applied in their presentation and analysis.

In dedicated hosting servers, the client chooses to lease an entire server to themselves. This server is not shared by another company. Organizations have full control over the infrastructure, including the operating system and hardware.

The service provider has a huge role in the whole deal – they manage security, memory, storage and tech support. This service is very proactive in nature. Dedicated hosting servers provide high performance, dedicated web hosting, stability and full control to business owners. However, due to the high cost, this service is used mostly by organizations that deal with a high volume of traffic on their websites.

There are some important questions you must ask before getting dedicated hosting services, like

  • Does their network infrastructure have multiple carriers and are they BGP4 optimized?
  • Are managed services available?
  • Does the dedicated hosting provider offer onsite technical support 24/7/365?
  • Does the hosting provider offer a Service Level Agreement (SLA)?
  • Does the provider offer any backup solutions?

Don’t get boggled by the service provider’s claims, choose the service based on your data needs.

The difference:

Big data is the science of analyzing high volumes of diverse data in near-real time (volume, velocity, variety). Typically, it involves using NoSQL technology and a distributed architecture to analyze the data. The analysis can be done in the public cloud or on private infrastructure. Big data is the leveraging of large amounts of raw data to get information that might not have been easy to get, before. For example, a store owner can tell how long someone stood looking at their displays by tracking the WiFi in a phone – even if it’s not connected. Hospitals might use this to find more information about how to keep patients safe, or identify health risks by linking together quantifiable information about patients that a human might not put together. (Quora)

When you compare, you see that big data servers use an asynchronous method in writing. These are not based on a constraint from the database engine. Thus, there are no delays in writing and the process is much faster than regular servers. In the case of other servers, the process is synchronous and categorized. Although it is a good step-by-step way of handling data, there are sometimes delays in the process caused by applications that are either not prepared or not built to hold this acknowledgment.

Big data is a comparatively new technology, so it is still in the developmental phase. The most commonly used platform for big data analytics is the open-source Apache Hadoop, which uses the Hadoop Distributed File System (HDFS) to manage storage. Distributed databases, including NoSQL or Cassandra, are also commonly associated with big data projects. These are relatively new technologies, and as such, come with some maturity problems.

“We’re just starting to figure out how to use it and what makes sense for us, and then trying to figure out how we best posture ourselves from an infrastructure standpoint to support it,” says Michael Passe, storage architect for Beth Israel Deaconess Medical Center (BIDMC) based in Boston. “I want to use the infrastructure because it’s not a Radio Shack science kit; it’s purpose-built to do this kind of thing and it does it very well,” Passe said. “Why would you want some generic thing with its own disks and a higher failure rate if you’ve already got Isilon in place?”

There is only one thing which may be a hurdle for several business owners when considering Big Data servers – the cost. It’s true that the software for big data platforms built on Hadoop is not costly, the hardware required to run it is where all the money gets involved. SQL database systems for large organizations can even rely on a few dedicated servers, which is not a dent in the wallet. As a result, small and medium-sized businesses turn to the cloud and shared hosting to meet their data demands.

In the end, however, the choice is completely based on how you see your IT infrastructure, desired cloud security services, data processing, handling and storage for your long-term projects. As the big data technology moves forward, there will be more options for business owners to embrace it without much thought.

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