Difference between Cloud Computing and Big Data Analytics | CS THEORY

Difference between Cloud Computing and Big Data Analytics

Cloud Computing: It is an on-demand delivery of resources like servers, databases, networking, software, analytics, applications and computational power over the Internet to promote speed and flexibility as well as the economy of scale. It helps in lowering operational costs and is much more reliable. Vast amounts of computing resources can be delivered within minutes or even less.

Big Data Analytics: It is the process of observing complicated patterns and relationships within large volumes of varied data, the big data, and using that analysis to make informed and effective business decisions. Large data sets are analyzed to draw conclusions about them.

Below is a table of differences between Cloud Computing and Big Data Analytics:

S.No.	Cloud Computing	Big Data Analytics
1	It is used to store large volume of data on remote server.	It processes large volume of data to draw patterns for decision making.
2	It is a computer paradigm/concept.	It is data analytics of varied and voluminous data.
3	It focuses on provisioning universal access of the services of an organisation.	It focuses on providing insights about data to govern better decision making.
4	Advantages include cost saving, reliability, centralized and on-demand.	Advantages include close to accurate and logical correlations for finer resolutions.
5	Various services are categorized into IaaS, PaaS and SaaS.	Various solutions include Hadoop, Ambari, Sqoop, MapReduce, Hive and Oozie.
6	It uses an extensive network of cloud servers over the Internet.	It is deployed either within the company’s data center or on the cloud.
7	It is required when swift deployment or scaling of applications while continuing centralized access.	It is required to analyze voluminous data and uses distributed framework with parallel computing.
8	It is a platform for accessing large data sets let alone the computation of it.	It is a process of cleaning, structuring and interpreting that data.
9	Stores data which is maintained by different service providers like AWS, Microsoft, Google, Dell, IBM etc. on remote servers.	Data is distributed among different computer systems and analysed by Cloudera, MapR, Apache etc.