The Magazine
Lokesh Vij
Lokesh Vij

Professor @ OPIT, Software Engineer @ Symantec, Faculty @ Seneca College. Location: Canada. Teaches Cloud Computing courses (BSc), Big Data and Cloud Computing Infrastructure (MSc).

The Basics of Cloud Computing: Examples and Applications
Lokesh Vij
Lokesh Vij
July 02, 2023 · min read

According to Statista, the U.S. cloud computing industry generated about $206 billion in revenue in 2022. Expand that globally, and the industry has a value of $483.98 billion. Growth is on the horizon, too, with Grand View Research stating that the various types of cloud computing will achieve a compound annual growth rate (CAGR) of 14.1% between 2023 and 2030.

The simple message is that cloud computing applications are big business.

But that won’t mean much to you if you don’t understand the basics of cloud computing infrastructure and how it all works. This article digs into the cloud computing basics so you can better understand what it means to deliver services via the cloud.

The Cloud Computing Definition

Let’s answer the key question immediately – what is cloud computing?

Microsoft defines cloud computing as the delivery of any form of computing services, such as storage or software, over the internet. Taking software as an example, cloud computing allows you to use a company’s software online rather than having to buy it as a standalone package that you install locally on your computer.

For the super dry definition, cloud computing is a model of computing that provides shared computer processing resources and data to computers and other devices on demand over the internet.

Cloud Computing Meaning

Though the cloud computing basics are pretty easy to grasp – you get services over the internet – what it means in a practical context is less clear.

In the past, businesses and individuals needed to buy and install software locally on their computers or servers. This is the typical ownership model. You hand over your money for a physical product, which you can use as you see fit.

You don’t purchase a physical product when using software via the cloud. You also don’t install that product, whatever it may be, physically on your computer. Instead, you receive the services managed directly by the provider, be they storage, software, analytics, or networking, over the internet. You (and your team) usually install a client that connects to the vendor’s servers, which contain all the necessary computational, processing, and storage power.

What Is Cloud Computing With Examples?

Perhaps a better way to understand the concept is with some cloud computing examples. These should give you an idea of what cloud computing looks like in practice:

  • Google Drive – By integrating the Google Docs suite and its collaborative tools, Google Drive lets you create, save, edit, and share files remotely via the internet.
  • Dropbox – The biggest name in cloud storage offers a pay-as-you-use service that enables you to increase your available storage space (or decrease it) depending on your needs.
  • Amazon Web Services (AWS) – Built specifically for coders and programmers, AWS offers access to off-site remote servers.
  • Microsoft Azure – Microsoft markets Azure as the only “consistent hybrid cloud.” This means Azure allows a company to digitize and modernize their existing infrastructure and make it available over the cloud.
  • IBM Cloud – This service incorporates over 170 services, ranging from simple databases to the cloud servers needed to run AI programs.
  • Salesforce – As the biggest name in the customer relationship management space, Salesforce is one of the biggest cloud computing companies. At the most basic level, it lets you maintain databases filled with details about your customers.

Common Cloud Computing Applications

Knowing what cloud computing is won’t help you much if you don’t understand its use cases. Here are a few ways you could use the cloud to enhance your work or personal life:

  • Host websites without needing to keep on-site servers.
  • Store files and data remotely, as you would with Dropbox or Salesforce. Most of these providers also provide backup services for disaster recovery.
  • Recover lost data with off-site storage facilities that update themselves in real-time.
  • Manage a product’s entire development cycle across one workflow, leading to easier bug tracking and fixing alongside quality assurance testing.
  • Collaborate easily using platforms like Google Drive and Dropbox, which allow workers to combine forces on projects as long as they maintain an internet connection.
  • Stream media, especially high-definition video, with cloud setups that provide the resources that an individual may not have built into a single device.

The Basics of Cloud Computing

With the general introduction to cloud computing and its applications out of the way, let’s get down to the technical side. The basics of cloud computing are split into five categories:

  • Infrastructure
  • Services
  • Benefits
  • Types
  • Challenges

Cloud Infrastructure

The interesting thing about cloud infrastructure is that it simulates a physical build. You’re still using the same hardware and applications. Servers are in play, as is networking. But you don’t have the physical hardware at your location because it’s all off-site and stored, maintained, and updated by the cloud provider. You get access to the hardware, and the services it provides, via your internet connection.

So, you have no physical hardware to worry about besides the device you’ll use to access the cloud service.

Off-site servers handle storage, database management, and more. You’ll also have middleware in play, facilitating communication between your device and the cloud provider’s servers. That middleware checks your internet connection and access rights. Think of it like a bridge that connects seemingly disparate pieces of software so they can function seamlessly on a system.


Cloud services are split into three categories:

Infrastructure as a Service (IaaS)

In a traditional IT setup, you have computers, servers, data centers, and networking hardware all combined to keep the front-end systems (i.e., your computers) running. Buying and maintaining that hardware is a huge cost burden for a business.

IaaS offers access to IT infrastructure, with scalability being a critical component, without forcing an IT department to invest in costly hardware. Instead, you can access it all via an internet connection, allowing you to virtualize traditionally physical setups.

Platform as a Service (PaaS)

Imagine having access to an entire IT infrastructure without worrying about all the little tasks that come with it, such as maintenance and software patching. After all, those small tasks build up, which is why the average small business spends an average of 6.9% of its revenue on dealing with IT systems each year.

PaaS reduces those costs significantly by giving you access to cloud services that manage maintenance and patching via the internet. On the simplest level, this may involve automating software updates so you don’t have to manually check when software is out of date.

Software as a Service (SaaS)

If you have a rudimentary understanding of cloud computing, the SaaS model is the one you are likely to understand the most. A cloud provider builds software and makes it available over the internet, with the user paying for access to that software in the form of a subscription. As long as you keep paying your monthly dues, you get access to the software and any updates or patches the service provider implements.

It’s with SaaS that we see the most obvious evolution of the traditional IT model. In the past, you’d pay a one-time fee to buy a piece of software off the shelf, which you then install and maintain yourself. SaaS gives you constant access to the software, its updates, and any new versions as long as you keep paying your subscription. Compare the standalone versions of Microsoft Office with Microsoft Office 365, especially in their range of options, tools, and overall costs.

Benefits of Cloud Computing

The traditional model of buying a thing and owning it worked for years. So, you may wonder why cloud computing services have overtaken traditional models, particularly on the software side of things. The reason is that cloud computing offers several advantages over the old ways of doing things:

  • Cost savings – Cloud models allow companies to spread their spending over the course of a year. It’s the difference between spending $100 on a piece of software versus spending $10 per month to access it. Sure, the one-off fee ends up being less, but paying $10 per month doesn’t sting your bank balance as much.
  • Scalability – Linking directly to cost savings, you don’t need to buy every element of a software to access the features you need when using cloud services. You pay for what you use and increase the money you spend as your business scales and you need deeper access.
  • Mobility – Cloud computing allows you to access documents and services anywhere. Where before, you were tied to your computer desk if you wanted to check or edit a document, you can now access that document on almost any device.
  • Flexibility – Tied closely to mobility, the flexibility that comes from cloud computing is great for users. Employees can head out into the field, access the services they need to serve customers, and send information back to in-house workers or a customer relationship management (CRM) system.
  • Reliability – Owning physical hardware means having to deal with the many problems that can affect that hardware. Malfunctions, viruses, and human error can all compromise a network. Cloud service providers offer reliability based on in-depth expertise and more resources dedicated to their hardware setups.
  • Security – The done-for-you aspect of cloud computing, particularly concerning maintenance and updates, means one less thing for a business to worry about. It also absorbs some of the costs of hardware and IT maintenance personnel.

Types of Cloud Computing

The types of cloud computing are as follows:

  • Public Cloud – The cloud provider manages all hardware and software related to the service it provides to users.
  • Private Cloud – An organization develops its suite of services, all managed via the cloud but only accessible to group members.
  • Hybrid Cloud – Combines a public cloud with on-premises infrastructure, allowing applications to move between each.
  • Community Cloud – While the community cloud has many similarities to a public cloud, it’s restricted to only servicing a limited number of users. For example, a banking service may only get offered to the banking community.

Challenges of Cloud Computing

Many a detractor of cloud computing notes that it isn’t as issue-proof as it may seem. The challenges of cloud computing may outweigh its benefits for some:

  • Security issues related to cloud computing include data privacy, with cloud providers obtaining access to any sensitive information you store on their servers.
  • As more services switch over to the cloud, managing the costs related to every subscription you have can feel like trying to navigate a spider’s web of software.
  • Just because you’re using a cloud-based service, that doesn’t mean said service handles compliance for you.
  • If you don’t perfectly follow a vendor’s terms of service, they can restrict your access to their cloud services remotely. You don’t own anything.
  • You can’t do anything if a service provider’s servers go down. You have to wait for them to fix the issue, leaving you stuck without access to the software for which you’re paying.
  • You can’t call a third party to resolve an issue your systems encounter with the cloud service because the provider is the only one responsible for their product.
  • Changing cloud providers and migrating data can be challenging, so even if one provider doesn’t work well, companies may hesitate to look for other options due to sunk costs.

Cloud Computing Is the Present and Future

For all of the challenges inherent in the cloud computing model, it’s clear that it isn’t going anywhere. Techjury tells us that about 57% of companies moved, or were in the process of moving, their workloads to cloud services in 2022.

That number will only increase as cloud computing grows and develops.

So, let’s leave you with a short note on cloud computing. It’s the latest step in the constant evolution of how tech companies offer their services to users. Questions of ownership aside, it’s a model that students, entrepreneurs, and everyday people must understand.

Read the article
Different Types of Cloud Computing Deployment Models & Services
Lokesh Vij
Lokesh Vij
June 28, 2023 · min read

It’s hard to find a person who uses the internet but doesn’t enjoy at least one cloud computing service. “Cloud computing” sounds complex, but it’s actually all around you. The term encompasses every tool, app, and service that’s delivered via the internet.

The two popular examples are Dropbox and Google Drive. These cloud-based storage spaces allow you to keep your files at arm’s reach and access them in a few clicks. Zoom is also a cloud-based service – it makes communication a breeze.

Cloud computing can be classified into four types: public, private, hybrid, and community. These four types belong to one of the three cloud computing service models: infrastructure as a service, platform as a service, or software as a service.

It’s time to don a detective cap and explore the mystery hidden behind cloud computing.

Cloud Computing Deployment Models

  • Public cloud
  • Private cloud
  • Hybrid cloud
  • Community cloud

Public Cloud

The “public” in public cloud means anyone who wants to use that service can get it. Public clouds are easy to access and usually have a “general” purpose many can benefit from.

It’s important to mention that with public clouds, the infrastructure is owned by the service provider, not by consumers. This means you can’t “purchase” a public cloud service forever.

Advantages of Public Cloud

  • Cost-effectiveness – Some public clouds are free. Those that aren’t free typically have a reasonable fee.
  • Scalability – Public clouds are accommodating to changing demands. Depending on the cloud’s nature, you can easily add or remove users, upgrade plans, or manipulate storage space.
  • Flexibility – Public clouds are suitable for many things, from storing a few files temporarily to backing up an entire company’s records.

Disadvantages of Public Cloud

  • Security concerns – Since anyone can access public clouds, you can’t be sure your data is 100% safe.
  • Limited customization – While public clouds offer many options, they don’t really allow you to tailor the environment to match your preferences. They’re made to suit broad masses, not particular individuals.

Examples of Public Cloud Providers

  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform

Private Cloud

If you’re looking for the complete opposite of public clouds, you’ve found it. Private clouds aren’t designed to fit general criteria. Instead, they’re made to please a single user. Some of the perks private clouds offer are exclusive access, exceptional security, and unmatched customization.

A private cloud is like a single-tenant building. The tenant owns the building and has complete control to do whatever they want. They can tear down walls, drill holes to hang pictures, paint the rooms, install tiles, and get new furniture. When needs change, the tenant can redecorate, no questions asked.

Advantages of Private Cloud

  • Enhanced security – The company’s IT department oversees private clouds. They’re usually protected by powerful firewalls and protocols that minimize the risk of information breaches.
  • Greater control and customization – Since private clouds are one-on-one environments, you can match them to your needs.
  • Improved performance – Private clouds can have functions that suit your organization to the letter, resulting in high performance.

Disadvantages of Private Cloud

  • Higher costs – The exclusive access and customization come at a cost (literally).
  • Limited scalability – You can scale private clouds, but only up to a certain point.

Examples of Private Cloud Providers

  • VMware
  • IBM Cloud
  • Dell EMC

Hybrid Cloud

Public and private clouds have a few important drawbacks that may be deal-breakers for some people. You may want to use public clouds but aren’t ready to compromise on security. On the other hand, you may want the perks that come with private clouds but aren’t happy with limited scalability.

That’s when hybrid clouds come into play because they let you get the best of both worlds. They’re the perfect mix of public and private clouds and offer their best features. You can get the affordability of public clouds and the security of private clouds.

Advantages of Hybrid Cloud

  • Flexibility and scalability – Hybrid clouds are personalized environments, meaning you can adjust them to meet your specific needs. If your needs change, hybrid clouds can keep up.
  • Security and compliance – You don’t have to worry about data breaches or intruders with hybrid clouds. They use state-of-the-art measures to guarantee safety, privacy, and security.
  • Cost optimization – Hybrid clouds are much more affordable than private ones. You’ll need to pay extra only if you want special features.

Disadvantages of Hybrid Cloud

  • Complexity in management – Since they combine public and private clouds, hybrid clouds are complex systems that aren’t really easy to manage.
  • Potential security risks – Hybrid clouds aren’t as secure as private clouds.

Examples of Hybrid Cloud Providers

  • Microsoft Azure Stack
  • AWS Outputs
  • Google Anthos

Community Cloud

Community clouds are shared by more than one organization. The organizations themselves manage them or a third party. In terms of security, community clouds fall somewhere between private and public clouds. The same goes for their price.

Advantages of Community Cloud

  • Shared resources and costs – A community cloud is like a common virtual space for several organizations. By sharing the space, the organizations also share costs and resources.
  • Enhanced security and compliance – Community clouds are more secure than public clouds.
  • Collaboration opportunities – Cloud sharing often encourages organizations to collaborate on different projects.

Disadvantages of Community Cloud

  • Limited scalability – Community clouds are scalable, but only to a certain point.
  • Dependency on other organizations – As much as sharing a cloud with another organization(s) sounds exciting (and cost-effective), it means you’ll depend on them.

Examples of Community Cloud Providers

  • Salesforce Community Cloud
  • Rackspace
  • IBM Cloud for Government

Cloud Computing Service Models

There are three types of cloud computing service models:

  • Infrastructure as a Service (IaaS)
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)


IaaS is a type of pay-as-you-go, third-party service. In this case, the provider gives you an opportunity to enjoy infrastructure services for your networking equipment, databases, devices, etc. You can get services like virtualization and storage and build a strong IT platform with exceptional security.

IaaS models give you the flexibility to create an environment that suits your organization. Plus, they allow remote access and cost-effectiveness.

What about their drawbacks? The biggest issue could be security, especially in multi-tenant ecosystems. You can mitigate security risks by opting for a reputable provider like AWS or Microsoft (Azure).


Here, the provider doesn’t deliver the entire infrastructure to a user. Instead, it hosts software and hardware on its own infrastructure, delivering only the “finished product.” The user enjoys this through a platform, which can exist in the form of a solution stack, integrated solution, or an internet-dependent service.

Programmers and developers are among the biggest fans of PaaS. This service model enables them to work on apps and programs without dealing with maintaining complex infrastructures. An important advantage of PaaS is accessibility – users can enjoy it through their web browser.

As far as disadvantages go, the lack of customizability may be a big one. Since you don’t have control over the infrastructure, you can’t really make adjustments to suit your needs. Another potential drawback is that PaaS depends on the provider, so if they’re experiencing problems, you could too.

Some examples of PaaS are Heroku and AWS Elastic Beanstalk.


Last but not least is SaaS. Thanks to this computing service model, users can access different software apps using the internet. SaaS is the holy grail for small businesses that don’t have the budget, bandwidth, workforce, or will to install and maintain software. Instead, they leave this work to the providers and enjoy only the “fun” parts.

The biggest advantage of SaaS is that it allows easy access to apps from anywhere. You’ll have no trouble using SaaS as long as you have internet. Plus, it saves a lot of money and time.

Nothing’s perfect, and SaaS is no exception. If you want to use SaaS without interruptions, you need to have a stable internet connection. Plus, with SaaS, you don’t have as much control over the software’s performance and security. Therefore, you need to decide on your priorities. SaaS may not be the best option if you want a highly-customizable environment with exceptional security.

The most popular examples of SaaS are Dropbox, Google Apps, and Salesforce.

Sit on the Right Cloud

Are high security and appealing customization features your priority? Or are you on the hunt for a cost-effective solution? Your answers can indicate which cloud deployment model you should choose.

It’s important to understand that models are not divided into “good” and “bad.” Each has unique characteristics that can be beneficial and detrimental at the same time. If you don’t know how to employ a particular model, you won’t be able to reap its benefits.

Read the article
The Advantages of Cloud Computing and Its Drawbacks
Lokesh Vij
Lokesh Vij
June 28, 2023 · min read

Gone are the days when you had to store boxes of documents in your office. Salvation came in the form of cloud computing in the 2000s. Since then, it’s made a world of difference for businesses across all industries, increasing productivity, organization, and decluttering the workspace. More importantly, it allows businesses to reduce various expenses by 30%-50%.

Cloud computing has countless benefits, but that doesn’t mean the technology is flawless. On the contrary, you should be aware of several disadvantages of cloud computing that can cause many problems with your implementation. Weighing up the pros and cons is essential – and we’ll do precisely that in this article.

Read on for the advantages and disadvantages of cloud computing.

Advantages of Cloud Computing

The cloud computing market is worth more than $540 billion. The main reason being that over 90% of all companies use some form of this technology. Here’s why they rely on cloud-based platforms.

Cost Efficiency

One of the greatest benefits of cloud computing is that it’s cost-efficient and allows you to reduce business expenses on three fronts.

Reduced Hardware and Software Expenses

You don’t need physical hardware to store your documents if you have a cloud computing platform. Likewise, the technology eliminates the need to run multiple software platforms because you can keep all your files in one place.

Lower Energy Consumption

In-house storage solutions can be convenient, but they consume a lot of electricity. Conversely, cloud computing systems help companies increase energy efficiency by over 90%.

Minimal Maintenance Costs

Maintaining such platforms is straightforward and affordable as cloud computing doesn’t involve heavy-duty software and hardware.

Scalability and Flexibility

Another reason cloud computing is popular is its scalability and flexibility. Here’s what underpins these advantages of cloud computing.

Easy Resource Allocation and Management

You don’t need to allocate your storage resources to numerous solutions if you have a unified cloud computing system. Managing your storage requirements becomes much easier with all your money going into one channel.

Pay-As-You-Go Pricing Model

Cloud-based platforms are available on a pay-as-you-go model. This reduces the risk of overpaying for your service because you’re only charged for the amount of data used.

Rapid Deployment of Applications and Services

Deploying cloud computing applications and services is simple. There’s no need for intense employee training, which further reduces your costs.

Accessibility and Mobility

Cloud computing is a highly accessible and mobile technology that can elevate your efficiency in a number of ways.

Access to Data and Applications From Anywhere

All it takes to access a cloud-based platform is a stable internet connection. As a result, you can retrieve key files virtually anywhere.

Improved Collaboration and Productivity

The ability to access data and applications from anywhere boosts collaboration and productivity. Your team gets a unified platform where they can share data with others much faster.

Support for Remote Work and Distributed Teams

Setting up a remote workspace is seamless with a cloud-computing solution. Employees no longer have to come to the office to perform repetitive tasks since they can do them from their computers.

Enhanced Security

If you want to address the most common security concerns in your organization, cloud computing is an excellent option.

Centralized Data Storage and Protection

By storing your information in a centralized location, you decrease the risk of data theft. In essence, you funnel all your resources into one platform rather than spread them out across multiple channels.

Regular Security Updates and Patches

Cloud computing providers offer regular updates to protect your information. Systems with the latest security patches are less prone to cyber attacks.

Advanced Encryption and Authentication Methods

You can also benefit from cloud computing tools due to their next-level encryption and authentication solutions. Most platforms feature AES 256-bit encryption, which is the most advanced and practically impregnable method. Furthermore, two-factor authentication lowers the chances of unauthorized access.

Disaster Recovery and Business Continuity

Business continuity and disaster recovery are two of the most pressing business challenges. Cloud computing solutions can help address these problems.

Automated Data Backup and Recovery

Many cloud storage systems are designed to automatically backup and recover your data. Hence, you don’t need to worry about losing your information in the event of a power outage.

Reduced Downtime and Data Loss

Since cloud computing helps prevent data loss, this technology also saves you less downtime. You don’t have to retrieve information manually because the platform does the work for you.

Simplified Disaster Recovery Planning

Although cloud computing tools are reliable, they’re not immune to failure caused by power loss, natural disasters, and other factors. Fortunately, these platforms have robust disaster recovery plans to get your system up and running in no time.

Disadvantages of Cloud Computing

Since the technology is so effective, you might be asking yourself: “Are there any disadvantages of cloud computing?” There are, and you need to understand these downsides to determine the best way to implement the technology. Here are the main drawbacks of cloud computing.

Data Privacy and Security Concerns

Like any other online technology, cloud computing can put users at risk of data privacy and security concerns.

Potential for Data Breaches and Unauthorized Access

While cloud apps have exceptional security practices, cyber criminals can bypass them with state-of-the-art technology and innovative hacking methods. Consequently, they may gain access to your information and steal your credentials.

Compliance With Data Protection Regulations

Your cloud computing tool may comply with many data protection regulations, but this doesn’t mean your information is 100% secure. Some standards only require apps to use robust password practices and fail to consider other attack methods, such as phishing.

Trusting Third-Party Providers With Sensitive Information

Online services require you to share your information to enable all features. Cloud computing is no different in this respect. You need to provide a third-party vendor with your data, which can be risky.

Limited Control and Customization

Cloud computing is a flexible and scalable technology. At the same time, it limits your control and customization options, which is why you might not be 100% happy with your platform.

Dependence on Cloud Service Providers

You decide what files you wish to share with your cloud-based solution. However, that’s pretty much it when it comes to the control you have over the platform. You depend on the vendor for every other aspect, including updates and patches.

Restrictions on Software and Hardware Customization

There aren’t many options to choose from when selecting a cloud storage plan. The price of your plan mostly depends on how much data you wish to share. Other than that, you get little-to-no hardware and software customization features.

Potential for Vendor Lock-In

Once you create an account with one cloud computing provider, you might not be happy with their services. As a result, you want to switch to a different platform. Many people think this is a simple transition, but that’s not always the case. Even though you can cancel your plan, migrating your data from one tool to the next can be difficult.

Network Dependency and Connectivity Issues

You might be relieved once you set up an account on a cloud-based platform: “I no longer need to clutter my office with masses of documents because I can now use an internet tool.” That said, using an online app also means you depend on network quality.

Reliance on Stable Internet Connection

A stable internet connection is essential for cloud computing. Internet problems can reduce or prevent you from accessing your files altogether.

Performance Issues Due to Network Latency

If your cloud network has high latency, sharing files can be challenging. In turn, latency reduces productivity and collaboration.

Vulnerability to Distributed Denial-of-Service (DDoS) Attacks

Cloud platforms are susceptible to so-called DDoS attacks. A cyber criminal can target your tool and keep you from accessing the service.

Downtime and Service Reliability

Not every cloud computing system performs the same in terms of reducing downtime and maximizing reliability.

Risk of Outages and Service Disruptions

While cloud-based solutions have exceptional recovery plans and backup methods, you’ll still face some downtime in case of outages. Even the shortest service disruption can cause major issues when working on certain projects.

Shared Resources and Potential for Performance Degradation

Cloud systems are convenient because they allow you to store your data in one place. Nonetheless, one of the key disadvantages of cloud computing is managing those shared resources. Accessing information can become difficult if you don’t stay on top of it.

Likewise, performance can drop at any point of your plan. App incompatibility and other issues can compromise data architecture and further compromise management.

Dependence on Provider’s Service Level Agreements (SLAs)

You’ll probably need to enter into an SLA when partnering with a cloud computing provider. These contracts can be rigid, meaning they may fail to recognize and adapt to evolving business needs.

Make an Informed Decision

Cloud computing has tremendous benefits, like improved data storage, collaboration, and cost reduction. The main drawbacks include hardware and software restrictions, connectivity issues, and potential downtime.

Therefore, you should understand the advantages and disadvantages of cloud computing before implementing a platform. Also, consider your business needs when partnering with a cloud provider to help prevent compatibility issues.

Read the article
RDBMS: An Introduction to the Relational Database Management System
Lokesh Vij
Lokesh Vij
June 26, 2023 · min read

When you first get into modern computing, one of the terms that comes up most frequently is relational databases. These are clusters that are organized in such a way that they effortlessly find links between connected data points.

Relational databases are convenient, but what happens when you deal with vast amounts of information? You need something to act as your North Star, guiding you through the network and allowing you to stay on top of the data.

That something is an RDBMS. According to Google, RDBMS stands for a relational database management system – software that sets up and manages relational databases. In its full form, it’s been the light at the end of the tunnel for thousands of companies due to its accuracy, security, and ease of use.

The definition and importance of RDBMSs are the tip of the iceberg when it comes to these systems. This introduction to RDBMS will delve a bit deeper by taking a closer look at the concept of RDBMS, the history of this technology, use cases, and the most common examples.

History of RDBMS

The concept of RDBMS might be shrouded in mystery for some. Thus, several questions may come up when discussing the notion, including one as basic as “What is RDBMS?”

Knowing the RDBMS definition is a great starting point on your journey to understanding this concept. But let’s take a few steps back and delve into the history of this system.

Origins of the Relational Model

What if we told you that the RDBMS concepts are older than the internet? It may sound surprising, but it’s true.

The concept of RDBMS was developed by Edgar F. Codd 43 years ago. He aimed to propose a more efficient way to store information, a method that would consume drastically less memory than anything at the time. His model was groundbreaking, to say the least.

E.F. Codd’s Paper on Relational Model

Codd laid down his proposal in a 1970s paper called “A Relational Model of Data for Large Shared Data Banks.” He advocated a database solution comprised of intertwined tables. These tables enabled the user to keep their information compact, lowering the amount of disk space necessary for storage (which was scarce at the time).

The rest is history. The public welcomed Codd’s model with open arms since it optimized storage requirements and allowed people to answer practically any question using his principle.

Development of SQL

Codd’s research paved the way for relational database management systems, the most famous of which is SQL. This programming language was also developed in the ‘70s and was originally named SEQUEL (Structured English Query Language). It was quickly implemented across the computing industry and grew more powerful as the years went by.

Evolution of RDBMS Software

The evolution of RDBMS software has been fascinating.

Early RDBMS Software

The original RDBMS software was powerful, but it wasn’t a cure-all. It was a match made in heaven for users dealing with structured data, allowing them to organize it with minimal effort. However, pictures, music, and other forms of unstructured information were largely incompatible with this model.

Modern RDBMS Software

Today’s RDBMS solutions have come a long way from their humble beginnings. A modern relational DBMS can process different forms of information with ease. Programs like MySQL are versatile, adaptable, and easy to set up, helping database professionals spearhead the development of practically any application.

Key Concepts in RDBMS

Here’s another request you may have for an expert in RDBMS – explain the most significant relational database concepts. If that’s your question, your request has been granted. Coming up is an overview of RDBMS concepts that explain RDBMS in simple terms.

Tables and Relations

Tables and relations are the bread and butter of all relational database management systems. They sound straightforward, but they’re much different from, say, elements you come across in Microsoft Excel.

Definition of Tables

Tables are where data is stored in an RDBMS. They’re comprised of rows and columns for easier organization.

Definition of Relations

Relations are the links between tables. There can be several types of relations, such as one-to-one connections. This form means a data point from one table only matches one data point from another table.

Primary and Foreign Keys

No discussion about RDBMS solutions is complete without primary and foreign keys.

Definition of Primary Keys

A primary key is the unique element of each table that defines the table’s rows. The number of primary keys in a table is limited to one.

Definition of Foreign Keys

Foreign keys are used to form an inextricable bond between tables. They always refer to the primary key of another table.


Much of database management is akin to separating wheat from the chaff. One of the processes that allow you to do so is normalization.

Purpose of Normalization

Normalization is about restoring (or creating) order in a database. It’s the procedure of eradicating unnecessary data for the purpose of cleaner tables and smoother management.

Normal Forms

Every action has its reaction. For example, the reaction of normalization is normal forms. These are forms of data that are free from redundant or duplicate information, making them easily accessible.

Popular RDBMS Software

This article has dissected basic relational database concepts, the RDBMS meaning, and RDBMS full form. To further shed light on the technology, take a look at the crème de la crème of RDBMS platforms.

Oracle Database

If you want to make headway in the database management industry, Oracle Database can be one of your best friends.

Overview of Oracle Database

Oracle Database is the most famous RDBMS around. The very database of this network is called Oracle, and the software comes in five different versions. Each rendition has a specific set of features and benefits, but some perks hold true for each one.

Key Features and Benefits

  • Highly secure – Oracle employs top-grade security measures.
  • Scalable – The system supports company growth with adaptable features.
  • Available – You can tap into the architecture whenever necessary for seamless adjustments.

Microsoft SQL Server

Let’s see what another powerhouse – Microsoft SQL Server – brings to the table.

Overview of Microsoft SQL Server

Microsoft SQL Server is a reliable RDBMS with admirable capabilities. Like Oracle, it’s available in a range of editions to target different groups, including personal and enterprise users.

Key Features and Benefits

  • Fast – Few systems rival the speed of Microsoft SQL Server.
  • Versatile – The network supports on-premise and cloud applications.
  • Affordable – You won’t burn a hole in your pocket if you buy the standard version.


You can take your business to new heights with MySQL. The following section will explore what makes this RDBMS a go-to pick for Uber, Slack, and many other companies.

Overview of MySQL

MySQL is another robust RDBMS that enables fast data retrieval. It’s an open-source solution, making it less complex than some other platforms.

Key Features and Benefits

  • Quick – Efficient memory use speeds up the MySQL environment.
  • Secure – Bulletproof password systems safeguard against hacks.
  • Scalable – You can use MySQL both for small and large data sets.


Last but not least, PostgreSQL is a worthy contender for the best RDBMS on the market.

Overview of PostgreSQL

If you need a long-running RDBMS, you can’t go wrong with PostgreSQL. It’s an open-source solution that’s received more than two decades’ worth of refinement.

Key Features and Benefits

  • Nested transactions – These elements deliver higher concurrency control.
  • Anti-hack environment – Advanced locking features keep cybercriminals at bay.
  • Table inheritance – This feature makes the network more consistent.

RDBMS Use Cases

Now we get to what might be the crux of the RDBMS discussion: Where can you implement these convenient solutions?

Data Storage and Retrieval

  • Storing large amounts of structured data – Use an RDBMS to keep practically unlimited structured data.
  • Efficient data retrieval – Retrieve data in a split second with an RDBMS.

Data Analysis and Reporting

  • Analyzing data for trends and patterns – Discover customer behavior trends with a robust RDBMS.
  • Generating reports for decision-making – Facilitate smart decision-making with RDBMS-generated reports.

Application Development

  • Backend for web and mobile applications – Develop a steady web and mobile backend architecture with your RDBMS.
  • Integration with other software and services – Combine an RDBMS with other programs to elevate its functionality.

RDBMS vs. NoSQL Database

Many alternatives to RDBMS have sprung up, including NoSQL databases. But what makes these two systems different?

Overview of NoSQL Databases

A NoSQL database is the stark opposite of RDBMS solutions. It takes a non-relational approach, which is deemed more efficient by many.

Key Differences Between RDBMS and NoSQL Databases

  • Data model – RDBMSs store structured data, whereas NoSQL databases store unstructured information.
  • Scalability – NoSQL is more scalable because it doesn’t require a fixed schema (relation-based model).
  • Consistency – RDBMSs achieve consistency through rules, while NoSQL models feature eventual consistency.

Choosing the Right Database for Your Needs

Keep these guidelines in mind when selecting your database platform:

  • Use an RDBMS for centralized apps and NoSQL for decentralized solutions.
  • Use an RDBMS for structured data and NoSQL for unstructured data.
  • Use an RDBMS for moderate data activity and NoSQL for high data activity.

Exploring the Vast Utility of RDBMS

If you’re looking for a descriptive answer to the “what is relational database management system question,” here it is – it is the cornerstone of database management for countless enterprises. It’s ideal for structured data projects and gives the user the reins of data management. Plus, it’s as secure as it gets.

The future looks even more promising. Database professionals are expected to rely more on blockchain technology and cloud storage to elevate the efficacy of RDBMS.

Read the article
Big Data Analytics: A Comprehensive Guide to Characteristics, Types, & Real-World Trends
Lokesh Vij
Lokesh Vij
June 24, 2023 · min read

The term “big data” is self-explanatory: it’s a large collection of data. However, to be classified as “big,” data needs to meet specific criteria. Big data is huge in volume, gets even bigger over time, arrives with ever-higher velocity, and is so complex that no traditional tools can handle it.

Big data analytics is the (complex) process of analyzing these huge chunks of data to discover different information. The process is especially important for small companies that use the uncovered information to design marketing strategies, conduct market research, and follow the latest industry trends.

In this introduction to big data analytics, we’ll dig deep into big data and uncover ways to analyze it. We’ll also explore its (relatively short) history and evolution and present its advantages and drawbacks.


History and Evolution of Big Data

We’ll start this introduction to big data with a short history lesson. After all, we can’t fully answer the “what is big data?” question if we don’t know its origins.

Let’s turn on our time machine and go back to the 1960s. That’s when the first major change that marked the beginning of the big data era took place. The advanced development of data centers, databases, and innovative processing methods facilitated the rise of big data.

Relational databases (storing and offering access to interconnected data points) have become increasingly popular. While people had ways to store data much earlier, experts consider that this decade set the foundations for the development of big data.

The next major milestone was the emergence of the internet and the exponential growth of data. This incredible invention made handling and analyzing large chunks of information possible. As the internet developed, big data technologies and tools became more advanced.

This leads us to the final destination of short time travel: the development of big data analytics, i.e., processes that allow us to “digest” big data. Since we’re witnessing exceptional technological developments, the big data journey is yet to continue. We can only expect the industry to advance further and offer more options.

Big Data Technologies and Tools

What tools and technologies are used to decipher big data and offer value?

Data Storage and Management

Data storage and management tools are like virtual warehouses where you can pack up your big data safely and work with it as needed. These tools feature a powerful infrastructure that lets you access and fetch the desired information quickly and easily.

Data Processing and Analytics Framework

Processing and analyzing huge amounts of data are no walk in the park. But they can be, thanks to specific tools and technologies. These valuable allies can clean and transform large piles of information into data you can use to pursue your goals.

Machine Learning and Artificial Intelligence Platforms

Machine learning and artificial intelligence platforms “eat” big data and perform a wide array of functions based on the discoveries. These technologies can come in handy with testing hypotheses and making important decisions. Best of all, they require minimal human input; you can relax while AI works its magic.

Data Visualization Tools

Making sense of large amounts of data and presenting it to investors, stakeholders, and team members can feel like a nightmare. Fortunately, you can turn this nightmare into a dream come true with big data visualization tools. Thanks to the tools, creating stunning graphs, dashboards, charts, and tables and impressing your coworkers and superiors has never been easier.

Big Data Analytics Techniques and Methods

What techniques and methods are used in big data analytics? Let’s find the answer.

Descriptive Analytics

Descriptive analytics is like a magic wand that turns raw data into something people can read and understand. Whether you want to generate reports, present data on a company’s revenue, or analyze social media metrics, descriptive analytics is the way to go.

It’s mostly used for:

  • Data summarization and aggregation
  • Data visualization

Diagnostic Analytics

Have a problem and want to get detailed insight into it? Diagnostic analytics can help. It identifies the root of an issue, helping you figure out your next move.

Some methods used in diagnostic analytics are:

  • Data mining
  • Root cause analysis

Predictive Analytics

Predictive analytics is like a psychic that looks into the future to predict different trends.

Predictive analytics often uses:

  • Regression analysis
  • Time series analysis

Prescriptive Analytics

Prescriptive analytics is an almighty problem-solver. It usually joins forces with descriptive and predictive analytics to offer an ideal solution to a particular problem.

Some methods prescriptive analytics uses are:

  • Optimization techniques
  • Simulation and modeling

Applications of Big Data Analytics

Big data analytics has found its home in many industries. It’s like the not-so-secret ingredient that can make the most of any niche and lead to desired results.

Business and Finance

How do business and finance benefit from big data analytics? These industries can flourish through better decision-making, investment planning, fraud detection and prevention, and customer segmentation and targeting.


Healthcare is another industry that benefits from big data analytics. In healthcare, big data is used to create patient databases, personal treatment plans, and electronic health records. This data also serves as an excellent foundation for accurate statistics about treatments, diseases, patient backgrounds, risk factors, etc.

Government and Public Sector

Big data analytics has an important role in government and the public sector. Analyzing different data improves efficiency in terms of costs, innovation, crime prediction and prevention, and workforce. Multiple government parts often need to work together to get the best results.

As technology advances, big data analytics has found another major use in the government and public sector: smart cities and infrastructure. With precise and thorough analysis, it’s possible to bring innovation and progress and implement the latest features and digital solutions.

Sports and Entertainment

Sports and entertainment are all about analyzing the past to predict the future and improve performance. Whether it’s analyzing players to create winning strategies or attracting the audience and freshening up the content, big data analytics is like a valuable player everyone wants on their team.

Challenges and Ethical Considerations in Big Data Analytics

Big data analytics represent doors to new worlds of information. But opening these doors often comes with certain challenges and ethical considerations.

Data Privacy and Security

One of the major challenges (and the reason some people aren’t fans of big data analytics) is data privacy and security. The mere fact that personal information can be used in big data analytics can make individuals feel exploited. Since data breaches and identity thefts are, unfortunately, becoming more common, it’s no surprise some people feel this way.

Fortunately, laws like GDPR and CCPA give individuals more control over the information others can collect from them.

Data Quality and Accuracy

Big data analytics can sometimes be a dead end. If the material wasn’t handled correctly, or the data was incomplete to start with, the results themselves won’t be adequate.

Algorithmic Bias and Fairness

Big data analytics is based on algorithms, which are designed by humans. Hence, it’s not unusual to assume that these algorithms can be biased (or unfair) due to human prejudices.

Ethical Use of Big Data Analytics

The ethical use of big data analytics concerns the “right” and “wrong” in terms of data usage. Can big data’s potential be exploited to the fullest without affecting people’s right to privacy?

Future Trends and Opportunities in Big Data Analytics

Although it has proven useful in many industries, big data analytics is still relatively young and unexplored.

Integration of Big Data Analytics With Emerging Technologies

It seems that new technologies appear in the blink of an eye. Our reality today (in a technological sense) looks much different than just two or three years ago. Big data analytics is now intertwined with emerging technologies that give it extra power, accuracy, and quality.

Cloud computing, advanced databases, the Internet of Things (IoT), and blockchain are only some of the technologies that shape big data analytics and turn it into a powerful giant.

Advancements in Machine Learning and Artificial Intelligence

Machines may not replace us (at least not yet), but it’s impossible to deny their potential in many industries, including big data analytics. Machine learning and artificial intelligence allow for analyzing huge amounts of data in a short timeframe.

Machines can “learn” from their own experience and use this knowledge to make more accurate predictions. They can pinpoint unique patterns in piles of information and estimate what will happen next.

New Applications and Industries Adopting Big Data Analytics

One of the best characteristics of big data analytics is its versatility and flexibility. Accordingly, many industries use big data analytics to improve their processes and achieve goals using reliable information.

Every day, big data analytics finds “new homes” in different branches and niches. From entertainment and medicine to gambling and architecture, it’s impossible to ignore the importance of big data and the insights it can offer.

These days, we recognize the rise of big data analytics in education (personalized learning) and agriculture (environmental monitoring).

Workforce Development and Education in Big Data Analytics

Analyzing big data is impossible without the workforce capable of “translating” the results and adopting emerging technologies. As big data analytics continues to develop, it’s vital not to forget about the cog in the wheel that holds everything together: trained personnel. As technology evolves, specialists need to continue their education (through training and certification programs) to stay current and reap the many benefits of big data analytics.

Turn Data to Your Advantage

Whatever industry you’re in, you probably have goals you want to achieve. Naturally, you want to achieve them as soon as possible and enjoy the best results. Instead of spending hours and hours going through piles of information, you can use big data analytics as a shortcut. Different types of big data technologies can help you improve efficiency, analyze risks, create targeted promotions, attract an audience, and, ultimately, increase revenue.

While big data offers many benefits, it’s also important to be aware of the potential risks, including privacy concerns and data quality.

Since the industry is changing (faster than many anticipated), you should stay informed and engaged if you want to enjoy its advantages.

Read the article