Edge vs. Cloud

First things first, before we get into detail about advantages and disadvantages of both, we first need definitions.

Definitions of Edge Computing and Cloud Computing

What is cloud computing?

Cloud computing is the provision of IT infrastructure as a service. This includes, for example, storage, databases, servers or software. The user usually only pays for the services that he actually uses.

Cloud hosted services don’t have to be installed locally on the user’s premises, but can be used by the clients via interfaces and programs such as web browsers. Users access their services via defined interfaces from any location with network coverage. It is no longer necessary to operate the user’s own IT infrastructure and install local software.

Cloud computing offers high security. Many cloud providers provide technologies or controls that ensure this protection. They also help to protect stored data from possible threats, for example. In addition, productivity speaks in favor of cloud computing. In contrast to local data centers, there are no significant setup and administration costs.

What is edge computing?

Edge computing is the decentralized processing of data that takes place at the edge of the network. This means that the data is not collected, analyzed or retrieved from a central server or in the cloud, but at local nodes.

Where is edge computing used?

Edge computing can be used, for example, in areas where a large amount of data must be processed in real time and within a short delay time. This includes, for example, the Internet of Things, autonomous driving or the management of energy networks. Edge computing is also used in Industry 4.0. There, edge computing is used for automated processes, for example.

Edge computing is altogether more risky, as serious damage could result from hacker attacks. Nevertheless, edge computing will be a very important tool in the future, especially for the Internet of Things.

What are the differences between cloud computing and edge computing?

Processing of data

  • Cloud computing: Decentralized on cloud/server
  • Edge Computing: Decentralized on the edge of the network

Types of data

  • Cloud Computing: Non-time-critical data
  • Edge computing: Time-critical data


  • Cloud Computing: High (long distance between user and application)
  • Edge computing: Low (short distance between user and application)


  • Cloud computing: For remote sites
  • Edge computing: For sites with limited or no connection to a central site.

As already considered, it can be advantageous to move data processing to the edge of the network in order to pre-sort the information according to usefulness and non-usefulness before sending it to the cloud or server. In this way, edge computing helps offload conventional computing systems.

When planning IoT structures in companies, the first question should always be, where information is absolutely necessary and where it can be dispensed with. Based on this, a decision is made for a suitable model, which may very well consist of an edge cloud solution. It is important for any data processing to observe legal regulations and internal company compliance. Data security is also an important aspect – here, for example, security modules with modern encryption standards can be used.

IoT boom makes edge computing necessary

According to various experts, the IoT market will explode in the coming years:

  • Gartner estimates that there were 6.4 billion connected devices in 2016, rising to 20.8 billion by 2020. They estimate that 5.5 million new “things” were connected every day in 2016.
  • IDC projects that global IoT revenue will grow from $2.71 billion in 2015 to $7.065 billion in 2020, with the installed device base reaching 28.1 billion in 2020.
  • IHS Markit forecasts that the IoT market will grow from 15.4 billion devices in 2015 to 30.7 billion devices in 2020 and 75.4 billion in 2025.
  • McKinsey estimates the total size of the IoT market at about $900 million in 2015 and will grow to $3.7 billion by 2020.

All of these “things,” of course, could communicate via the cloud. However, the sheer mass of data that will be generated as devices communicate is problematic. It’s not just about the strain on computing capacity, but also latency. Imagine what just minimal drops in Internet connectivity will do to microtransactions that are expected to run thousands of processes in a matter of seconds.

Out of this problem comes the need for edge computing.

Edge computing is the opposite of cloud computing. It refers to decentralized data processing at the edge of the network. Data is therefore not retrieved from the central cloud, but is bundled at local nodes where it can be accessed by “things”.

For example, an autonomous vehicle that gets location and congestion information from a nearby node doesn’t have to run a data query through a data center hundreds or thousands of miles away that has to process millions of other requests that have nothing to do with traffic. So the nodes provide information for a specific area, taking the burden off the cloud.

The growing IoT market will make edge computing increasingly important. But it is also clear that cloud and edge computing are not mutually exclusive technologies, but cooperate explicitly.