On-Premise

Programs that a company uses have to run somewhere. So they need computers, storage space, and a constant power supply. With On-Premise, these computers are located in-house, usually in a room specifically set up for that purpose. The company buys the equipment, maintains it itself, and bears full responsibility for it. The term comes from English and literally means “on one’s own property.” The counter-model is the cloud: there, one rents computing power from a provider such as Amazon or Microsoft and accesses it over the internet.

Control over one’s own data

The most important reason for owning one’s own computers is confidentiality. A hospital manages patient records, a bank manages account transactions, a machine builder manages design drawings. No one wants such data sitting on someone else’s hard drives. Whoever owns the computers themselves knows exactly where the data is and who can access it.

On top of that come legal requirements. In Germany and the EU there are strict rules about where personal data may be stored. With an American cloud provider, the legal situation is complicated, because US authorities can, under certain conditions, demand access. Having one’s own servers in one’s own basement makes this question simpler. That is why On-Premise remains more widespread among government agencies, hospitals, and defense companies than among start-ups.

Another argument is independence. Anyone who runs everything with a single provider is dependent on that provider’s prices and decisions. If the provider raises its fees, one has hardly any choice. Experts call this being stuck vendor lock-in, meaning dependence on a single supplier.

Server rack, air conditioning, maintenance team

In practice, On-Premise means: the company buys servers, i.e., especially powerful computers without a screen. These stand in metal racks in a cooled room, because they generate a lot of heat. This also requires emergency power supply and a fast network connection. Ongoing operation requires staff who install updates and fix outages.

The cost structure differs significantly from the cloud. On-Premise requires a large investment upfront, after which mainly electricity and personnel costs arise. In the cloud, one pays nothing in advance, but receives a bill every month based on usage. With steady utilization over many years, owned hardware can be cheaper. With strongly fluctuating demand, renting is almost always more sensible.

A common misconception is that On-Premise is automatically more secure. That only holds true if someone actually maintains the systems. A forgotten server with outdated software is an easy target for attackers. Large cloud providers, by contrast, employ entire security departments. Security therefore depends less on location than on diligence.

AI models in one’s own data center

In the news, the term currently appears mainly in connection with artificial intelligence. Many companies want to use language models without sending their internal documents to an external service. That is why there are freely available models that can be run on one’s own graphics cards. Providers such as Meta or Mistral deliberately publish such models for download.

This, however, is expensive. The graphics cards needed for AI computations often cost several tens of thousands of euros apiece. A powerful model requires several of them simultaneously. Small companies therefore resort to hybrid forms: non-critical tasks in the cloud, sensitive data in-house. Experts then speak of a hybrid solution.

One also constantly encounters the word outside of AI. Software makers such as SAP or Microsoft sell their products in both variants and have for years been pushing their customers toward the cloud, because recurring rental income is more predictable for them. When a corporation announces it is “migrating its systems from On-Premise to the cloud,” behind that often lies a project spanning several years and many millions of euros.