Edge Computing vs. Cloud Computing and Why It Matters

As distributed computing gains popularity, terms like cloud computing and edge computing are becoming more common. These are not just useless buzzwords to spark interest in a trend, but existing technologies that drive innovation in all sectors.

Cloud computing and edge computing are crucial components of the modern IT system. But what exactly do these technologies entail? And how do they compare to each other? Let’s find out.

An Introduction to Cloud Computing

We all have Dropbox or . used A disc to backup our important files and data. It is said that the data is stored in the “Cloud”, but what does this mean?

Simply put, the cloud is a collection of computing resources that can be accessed over the Internet. The idea is that on an industrial scale you can use hardware anywhere in the world cheaply and safely.

Traditionally, companies have been forced to set up and maintain large servers for their internal computing needs. This comes at a high cost, not to mention the lack of flexibility. By moving an application to the cloud, a company can abstract the hardware backend and request as many resources as it needs.

It has become routine for websites and other applications to be operated entirely from the cloud, which greatly simplifies the technology stack. Services such as Amazon AWS and Microsoft Azure are frontrunners in this area, driving a variety of applications for businesses around the world.


  • scalable: Cloud services can be ramped up as needed, making applications flexible without hard investments.
  • Cheap: It is more cost effective for a service provider to run large centralized server farms than it is for any company to set up its own computers. As a result, cloud services can be made available at a much lower cost than with traditional setups.
  • Easy: Setting up and managing an internal database and API backend is not easy. It is easier to abstract the hardware and request computing resources if necessary.


  • Network dependent: The main problem with cloud services is complete network dependency. Cloud services are not a solution for remote areas with poor network connectivity.
  • Slowly: Depending on the location of the cloud servers, communication can take a few seconds to a few minutes. That delay is too great for applications that require immediate decisions (such as industrial equipment).
  • Bandwidth Intensive: Since the cloud servers are responsible for the computation and storage, a lot of data has to be sent. Bandwidth requirements are expensive in information generating scenarios (AI, video recording, etc.).

Edge Computing Explained

One problem with cloud computing is its dependency on the network. This is not a problem for most tasks, but some applications are extremely time sensitive. The delay in sending data, performing processing in the cloud, and receiving results is small but noticeable.

Then there is the issue of bandwidth. Applications with video processing or AI algorithms work with large amounts of data, which can be expensive to send to the cloud. Especially if the data collection takes place at a remote location, where network connectivity is limited.

Edge computing offers an answer to these problems. Instead of sending the data to a server on the other side of the world, it is stored and processed on-site, or at least at a nearby location.

This has the advantage of saving data transfer costs and eliminating the network latency factor. The calculation can be done immediately and gives the results in real time, which is vital for many applications.


  • No latency: Since the edge computer resides at the data source, there is no network latency to deal with. This gives immediate results, which is important for real-time processes.
  • Reduced data transfer: The edge computer can process most of the data on-premises and only send the results to the cloud. This helps to reduce the volume of data transfer required.


  • More expensive than Cloud: Unlike cloud computing, edge computing requires a dedicated system on each edge node. Depending on the number of such nodes in an organization, costs can be much higher than cloud services.
  • Complex setup: With cloud computing, all we need to do is request resources and build the frontend of the application. The core of the hardware that executes these instructions is left to the cloud service provider. However, with edge computing, you have to build the backend taking into account the needs of the application. This makes it a much more complicated process.

Cloud Computing vs. Edge Computing: Which Is Better?

The first thing to understand is that cloud computing and edge computing are not competing technologies. They are not different solutions to the same problem, but completely different approaches that solve different problems.

Cloud computing is best for scalable applications that need to be scaled up or phased out according to demand. For example, web servers may demand additional resources during periods of high server load, ensuring seamless service without permanent hardware costs.

Likewise, edge computing is suitable for real-time applications that generate a lot of data. For example, Internet-of-Things (IoT) deals with: smart devices connected to a local network. These devices do not have powerful computers and must rely on an edge computer for their compute needs. Doing the same with the cloud would be too slow and unfeasible due to the large amounts of data involved.

In short, both cloud and edge computing have their use cases and should be chosen based on the application in question.

The hybrid approach

As we have said before, cloud computing and edge computing are not competitors, but solutions to different problems. That begs the question; can they both be used together?

The answer is yes. Many applications take a hybrid approach, integrating both technologies for ultimate efficiency. For example, industrial automation machines are usually connected to an on-site embedded computer.

This edge computer is responsible for operating the device and performing complex calculations without delay. But at the same time, this computer also sends limited data to the cloud, which runs the digital framework that manages the entire operation itself.

In this way, the application takes full advantage of the strengths of both approaches, relying on edge computing for real-time computations while using cloud computing for everything else.

What is the best distributed computing technology?

Edge computing is not an improved version of cloud computing. It is a different approach to distributed computing that is useful for time-sensitive and data-intensive applications.

However, cloud computing is still the most flexible and cost-efficient approach for most other applications. By offloading storage and processing to a dedicated server, businesses can focus on their operations without worrying about backend deployment.

Both are essential tools in a savvy IT professional’s repertoire, and most advanced facilities, whether IoT or otherwise, use a combination of the two technologies to achieve the best results.

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