The role of cloud computing in Big Data

What is the cloud?

Cloud is most common in the last few years. Everyone knows about the cloud, but in today’s post, we will discuss cloud in the context of big data. Cloud computing is a method of providing computer resources are shared for the applications that require flexible resources. These resources include application, storage, computing, networking, development, and deployment platforms. The Foundation of cloud computing is that it’s shared resources and distributed to end users as a service.

Examples of cloud computing and big data are Google and Both offer big data with the help of cloud.

There are 2 different cloud deployment models: 1) Public Cloud and Private Cloud).

Public Cloud

Public Cloud is down tầệung cloud was built by commercial vendors (Amazon, Rackspace, …) to create 1 data center high scalability to help hide the complex infrastructure with clients and provide different services.

Private Cloud

Private Cloud is a cloud infrastructure built by 1 Organization, they self-manage scalability of the internal data center.

Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:

Hybrid Cloud

Hybrid Cloud is the cloud infrastructure to be built with 2 or more clouds such as public and private cloud. Hybrid cloud brings the best of many cloud deployment models.


Cloud and big data-common properties

There are many characteristics of the Cloud Architecture and Cloud Computing which is also a critical take for big data.

List the characteristics of cloud computing that’s important in big data:

٠ Scalability


٠Ad-hoc Resource Pooling

٠Low Cost to Setup Infrastructure

٠Pay upon Use or Pay as you Go

٠Highly Availability

The leading provider of cloud for big data


Amazon to be the providers of Infrastructure as a Service (IaaS) the most common. The history of this begins quite interesting. They start with a pile of business support infrastructure down. Gradually they master its resources not be used most of the time. They decided to maximize the resources are there and so they brought out the Amazon service is an acronym for the Elastic Cloud (Amazon EC2) in 2006. Their products have grown a lot in recent times and now it has become one of the main business on the side selling probably.

٠Amazon also offers big service data in Amazon Web Services.

٠Here is the list of services in the Amazon Web Services:

٠Amazon Elastic’s MapReduce-handling very large data volumes.

٠Amazon DynammoDB-NoSQL DATABASE services.

٠Amazon Simple Storage Services (S3) – data storage service online

٠Amazon High-Performance Computing-providing high-performance computing clusters

٠Amazon services-RedShift data warehouse every petabyte scalability


Although Google is best known for its Search Engine, we also know the airline can offer more than that.

٠Google is an acronym for Engine-provides secure, flexible calculations from data center energy efficient use.

٠Google Big Query-allows SQL-like queries run with very large data sets.

٠Google Prediction API-tools of machine learning based on the cloud

Other providers

Next to Amazon and Google, we also have many other vendors about big data. Microsoft also joined big data with Microsoft Azure. In addition, Rackspace and NASA together OpenStack start. OpenStack’s goal is to provide cloud easy extension can run on any hardware.

Things to monitor

The cloud-based solutions provide excellent integration with 1 story big data as well as very economical to make. However, there are some things that should be considered when implementing big data on cloud solutions.

٠Data Integrity

٠Initial Cost

٠Recurring Cost


٠Data Access Security



Each company has a big data different approaches and have different laws and rules. Based on various factors, can install big solutions customized to their own data on the cloud.


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