Cloud computing vs edge computing

Processing an exponential amount of data involves ever more sophisticated calculation solutions. While just a few years ago cloud computing was the only alternative, edge computing has quickly moved from being an outsider to a favourite. What do the concepts of cloud and edge computing mean? What are their respective advantages and disadvantages? Should you choose cloud computing or edge computing? Should these two techniques be considered exclusive or complementary? We will arbitrate the cloud vs. edge computing match for you.


What is cloud computing?

Cloud computing is a method of processing computer data that relies on the use of data centers or external servers to process, analyse, and store data. The information therefore travels continuously between the user and the data centers.

Currently, cloud computing remains the preferred data processing method for many.

Advantages and disadvantages of cloud computing

One of the greatest advantages of cloud computing is the flexibility of the service. The computing power can be adapted and modulated as required. In addition, the sharing of computing resources gives access to on-demand services such as IaaS (Internet as a Service), PaaS (Platform as a Service) or SaaS (Software as a Service).

Cloud computing enables collaboration without physical proximity and the sharing of applications and interfaces. The year 2020 has fully demonstrated its usefulness.

Thanks to cloud computing, companies have the opportunity to better manage their costs and benefit from resources that would otherwise be unaffordable. Security and maintenance issues are delegated to a third-party company. Cloud computing therefore remains a must for most companies.

Cloud computing has two major disadvantages:

  • Latency: the geographical location of data centres is often far from the data entry point. There is therefore a latency time in processing. This minimal latency time often remains imperceptible to the human being. Nevertheless, it can lead to difficulties when data must be processed in real time. The classic example is that of connected cars where a millisecond delay can cause an accident ;
  • The use of bandwidth: incessant communications between servers and users use up bandwidth and could eventually saturate it. Scalability constraints are therefore very present.

More generally, cloud computing does not appear to be the ideal solution in the age of the Internet of Things.


What is edge computing?

Edge computing is a mode of data processing that aims to carry out operations as close as possible to the source of the data. We are talking about physical proximity here. Computing takes place at the edge of the network, which reduces latency times. Edge computing therefore involves a local infrastructure in the form of hardware or equipment (computer, server, router, drone, etc.). This equipment is similar to micro data centers.

The rise of connected objects and the development of the Internet of Things have shown the limits of cloud computing. The number of connected objects is estimated at 20 billion in 2020. According to some sources, the number of connected objects will reach 64 billion in 2026. The consulting firm Deloitte is even talking about the possibility of approaching 500 billion connected objects by 2030. All of these objects communicate Machine to Machine (M2M). The amount of data constantly transmitted is such that a remote calculation method is no longer suitable. Edge computing, which goes hand in hand with 5G technology, is therefore essential to enable this evolution.

Advantages and disadvantages of edge computing

Edge computing reduces latency times, which guarantees fast data processing. Physical proximity reduces data transmission costs.

Edge computing is an inherent part of the development of various technologies where a millisecond makes the difference. In addition to connected cars, there are of course remote surgery applications.

The disadvantages of edge computing include the following:

  • Loss of data due to destruction, damage or theft of equipment or hardware;
  • Increased risk of cyber attacks and therefore high security costs. Indeed, edge computing equipment is a gateway to the network. Nevertheless, the company retains control of the data and remains in control of its security, which many people prefer, particularly when processing private data;
  • Costs in terms of infrastructure and equipment.

Cloud computing vs. edge computing

Edge computing and cloud computing are not mutually exclusive. Each method of computing has its advantages and should therefore be considered complementary. A good network infrastructure will be able to take advantage of and combine both technologies to provide the necessary flexibility for the business.

As mentioned earlier, cloud computing has bandwidth limitations, so edge computing allows you to maintain the existing infrastructure while expanding the range of possibilities. Edge computing can therefore be seen as a form of response to the challenge of scalability.

The trade-off between cloud computing and edge computing must be made on a case-by-case basis and a combination of the two modes of calculation will often be the appropriate response. To determine which network architecture to use, an enterprise must ask itself the following questions:

  • What type of data will I process?
  • What is my objective?
  • What is the available budget?
  • Is the data highly confidential?
  • How can I deal with data loss?
  • What is the volume of data to be processed?

The answers to these questions will generally lead to one method of calculation being preferred over another.

Aware of the importance of the cloud computing – edge computing tandem, Ryax has designed a data processing platform adapted to hybrid infrastructures. Ryax adopts all new generation technologies in order to provide SaaS data engineering with ever-increasing performance.


Do not hesitate to contact us if you plan to integrate the Ryax platform into your network architecture.

The Ryax Team.