Big Data vs. Cloud Computing

Currently, we are living in an era of network and data. We produce and face a part of information consistently (yes, every day!). Alongside this phenomenon, we are presently seeing a blast of data created through web-based life (like social media), messaging, emails, etc. Companies and people are exploring a maze of ever-expanding data that can be hard to meander through.

In this write-up, we’ll discuss one of the most frequent questions in an IT person that is Big Data vs. Cloud Computing or difference between Big Data and Cloud Computing. Not only the difference, but I will also try to answer some more queries related to these two technical terms.

Let’s begin!

Before discussing the differences between Big Data and Cloud Computing, let’s get into the definitions of the two technologies.

What is Big Data?

Big data is known as the synonym of enormous information that is, a big volume of data. If we start counting the data we have gathered since the very beginning of computers, you will realize that the growth of data from that year till now is really huge! It’s not in numbers or GB’s or TB’s but it is in more than 1000 TB’s that are Yottabytes. Really? 

Let me help you understand file sizes. Following is the sequence of file sizes:

  • Bit
  • Byte
  • KiloByte
  • MegaByte
  • GigaByte
  • TeraByte
  • Peta Byte
  • Exa Byte
  • Zetta Byte
  • Yotta Byte





1 bit



4 bits

1/2 (rare)


8 bits



1024 bytes



1, 024kilobytes

1, 048, 576


1, 024 megabytes

1, 073, 741, 824


1, 024 gigabytes

1, 099, 511, 627, 776


1, 024 terabytes

1, 125, 899, 906, 842, 624


1, 024 petabytes

1, 152, 921, 504, 606, 846, 976


1, 024 exabytes

1, 180, 591, 620, 717, 411, 303, 424


1, 024 zettabytes

1, 208, 925, 819, 614, 629, 174, 706, 176

Coming back to the topic, the volume of unstructured data specifically is expanding on account of different online networking platforms. Facebook alone produces more than 500 terabytes of new data consistently. With Twitter, the figure is 12 terabytes for each day. Much more of this information is basic to organizations since it furnishes them with the data that is vital to their business: What do my clients consider me and the opposition? What items and administrations do they need? What's more, what are the markets drift later on? By distinguishing patterns, the solution gives clients decisions about future turns of events. Such estimates give an information advantage over the opposition. They permit an early evaluation of potential approaches and structure a solid data reason for vital choices of organizations.


What is Cloud Computing?

Cloud computing is the delivery of on-demand services from applications to storage and processing power. Typically it is taken over the internet on a pay-as-you-go basis. To understand it better, consider the illustration of a taxi company like Uber. The people who cannot own their car or vehicle they can rent a taxi from Uber easily. There are similar examples like a rented house, a rented hotel room, etc. Similar is cloud computing. You need not buy the whole cloud infrastructure but can use the services on a pay-as-you-go basis. You only need to pay for the services you want to use. To avoid the upfront cost and complexity of owning and maintaining the cloud or IT infrastructure, organizations simply pay for what and when they use it. Cloud computing offers vast services like basics of storage, networking, and processing power through Natural Language Processing (NLP) and Artificial Intelligence (AI).

Differences between Big Data and Cloud Computing

Big Data vs. Cloud Computing


Big Data

Cloud Computing


It’s a terminology used to describe a large volume of data and information.

It’s a technology used to store data and information on a remote server rather than on a physical hard drive.


It refers to structured, semi-structured, or unstructured data that can be further processed for analysis

Cloud refers to the internet which in this case, acts as an infrastructure as a service.


Computers are used to unlock patterns from the data sets that are further analyzed to provide business insights.

It utilizes a vast network of cloud servers over the internet to analyze data and information, instead of using a personal computer or local server.


It includes all kinds of data in many different formats.

It’s a new paradigm for computing resources.


Big data can exist without cloud computing.

Cloud requires big data for computing resources.


The primary focus is on solving problems when a large amount of generating and processing data.

The primary focus is to provide computing resources and services with the help of the internet or network connection.


It breaks a large amount of data and distributes across various systems where data analysis and processing can be done.

Data is stored in the servers that are maintained by various service providers.


Cost-effective parallelism, scalable, robust are the main advantages.

Low maintenance expenses, centralized platform, provision for backup, and recovery are the main advantages.


Data variety, data storage, data integration, data processing, and resource management are challenges.

Availability, transformation, security, charging model are the challenges.  


It works with the internet is used to provide cloud-based services.

It works with distributed computing is used to analyze the data and produce more useful data. 


How Big Data and Cloud Computing go hand in hand

Marketing, sales, risk management, operations management, customer care, and substantially more: on account of big data analysis with cloud computing, organizations from various business regions get the definitive knowledge – in all ventures and independently. Cloud computing permits you to store mass information and make it accessible whenever required. It is, in this way, both a driver and a solution technology for managing huge information. 

In any case, it is the real-time analysis of the data gathered that makes an incentive for the business. It empowers organizations to acquire explicit data and consequently to respond a lot quicker to market and client needs and to plan inside organization forms all the more proficiently. For instance, demonstrative data from the car business gives early signs of irregularities, with the goal that workshops can educate drivers proactively and offer them a review arrangement. Data and correspondence technology are subsequently turning into a decisive factor for progress and productivity particularly in the case of IT since when managing huge information most databases rapidly arrive at their limits.

How Cloud Computing is helpful in Big Data projects?

As the data is growing constantly, the projects are also getting more complex. To keep it to be useful for the organizations, Big Data solutions must be implemented in a scalable and efficient manner. The most impactful feature of using cloud computing for big data projects is – Real-time data collection. It enables organizations to analyze data more deeply and reliably than before. A popular service like AWS (Amazon Web Services) has introduced a business scenario in the following manner:

  • Real-time log analysis
  • Social-media trend analysis
  • Financial analysis
  • Gaming and media developments
  • Fast queries and high performance
  • Scalability
  • Reduced overheads and no up-front cost
  • Fault tolerance


As per IBM, Big Data and Cloud Computing are known as the ideal combination. On average, 2.5 billion gigabytes of data are created daily, consisting of 200 million tweets and 30 billion pieces of content shared on Facebook each month. Big Data and Cloud Computing are still in constant evolution and are known as the great combo. Together, they provide a cost-effective and scalable infrastructure to support a great amount of data with business analytics. Therefore, the use of an appropriate solution is a basic requirement for many companies in order to stay with the competition. Stay communicative with the cloud!



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