Edge computing vs. cloud computing is a discussion that we need to start as embedded system experts. After all, these are two sides of the same coin, both effective in particular scenarios. If we add the fact that it’s possible to build a hybrid system, we end up with three options that we need to choose from depending on the circumstances. In this article, we will delve into the relationship between edge computing and cloud computing and explain the key differences between them. If this topic sparks your interest, then we invite you to read on.

Defining Edge Computing vs. Cloud Computing

We will begin our discussion by briefly explaining what each of these terms means.

  • Edge computing – This is an architecture that focuses on storing and accessing data near the power source, thus increasing the efficiency of the whole system. You can read more about it in our article titled “What Is Edge Computing? Everything You Need to Know”.
  • Cloud computing – This architecture requires access to the internet. In it, everything is stored online in a cloud, including servers, storage, databases, networking, software, analytics, and intelligence. It’s a centralized approach contrary to edge computing.

What Describes the Relationship between Edge Computing and Cloud Computing? The Differences Explained

As can be observed purely by analyzing the two short definitions of edge computing vs. cloud computing, they are opposite approaches to data storage. Both have their pros and cons and in many cases they work so differently that in a particular situation, a feature might be an advantage, while in a different one, the same feature might be a disadvantage. Let’s discuss it more closely.

Data Processing

Starting from data processing, this is something that puts edge computing vs. cloud computing on two different poles. Edge computing, due to the data stored locally, is much quicker and makes it possible to achieve nearly real-time data processing. Cloud computing, on the other hand, requires data to be transferred to/from the central cloud, so it is much slower. Therefore, here we can clearly say that edge computing is better in this aspect.


When it comes to the internet connection…cloud computing requires one that is reliable. This might mean additional costs or challenges, though the responsibility to provide access to the internet may be transferred to the final users, so it is not always a problem. 

Edge computing, unlike cloud computing, doesn’t require an internet connection. However, this still makes it more difficult to update, so it’s not always an advantage. The truth is that, in this case, edge computing doesn’t give you an edge if you need to update your device frequently. But, if you don’t, then it might be a better choice – after all, why should you (or the final user) bother with providing access to the internet?


Although the previous differences were mostly in favor of edge computing, this changes when it comes to workloads. In cloud computing, it’s possible to process dynamic, large datasets; in edge computing, it’s not. It is so because the latter is usually based on DSPs, simple processors that cannot handle more complex tasks.

Data Security

Cloud computing provides less data security vs. edge computing. It is so because the information needs to be transferred, which creates additional touchpoints that potential attackers could abuse. Plus, all the data is stored in one place, so a single leak could wreak true havoc.

Data Law Compliance

Cloud computing also faces one more issue when it comes to the data itself – it has to be in line with the laws of all the regions that the data is collected from. GDPR in the EU, state laws in the US, PIPL in China, APPI in Japan, Australian Privacy Act in Australia – by storing data in a cloud, you have to adhere to all these laws at the same time, which might be both expensive and difficult. Edge computing offers an alternative: you store data on the devices, so you need to worry only about the local law in the region where your embedded system is sold.

Data Accessibility

The case of data accessibility depends on who or what requires the data. If we mean the device that collects data, then edge computing wins vs. cloud computing. However, if you intend for the data to be accessed by a third party or a different device, cloud computing is the preferable option. This is because once information is stored in the cloud, the original device becomes less crucial. Even in the absence of an internet connection on the initial device, the data remains securely saved in the cloud, ensuring easy access for any subsequent device that requires it.

Cloud Computing vs. Edge Computing: Use Cases

So, when is cloud computing and edge computing applied? Here’s a list for both of them:

  • Edge computing:
    • drones,
    • patient monitoring systems,
    • autonomous vehicles.
  • Cloud computing:
    • image recognition systems,
    • AI as a service (AIaaS),
    • online education,
    • healthcare documentation systems.

The Takeaway

So, you know what describes the relationship between edge computing and cloud computing. If you need help with the former, don’t hesitate to contact us! Our edge computing services will be the perfect choice if you need a professionally designed, quick, and easily accessible data architecture in your embedded system!

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