Colocation Vs On Premise

Colocation Vs On Premise

As the world moves into a new era of information and technology, data collection, processing, and analysis will be in higher demand than ever, as Datasite Orlando says. Companies must purchase servers and data centers in order to be fitted with the requisite facilities to deal with vast amounts of data. In this regard, they have a variety of choices when it comes to the type of facilities they can use. In this article, we’ll discuss two highly ideal options: colocation and on premise data services. 

Colocation vs On Premise

To be able to compare and contrast colocation and on premise services, you must first understand their fundamental principles. However, one thing stands out right away: their similarities. 

The main similarity of the two data infrastructure systems is that they both require physical equipment and hardware that have to be maintained and physically accessed. These are two excellent options for companies that would prefer their data stored and processed in tangible equipment compared to hosting data on a cloud. 

However, the two ways also come with distinct differences. 


The colocation provider simply rents out a room in their building in a colocation setup. The organization also has to purchase the requisite data infrastructure equipment. The company, on the other hand, profits from the opportunity to set up their equipment in a room that has already been built to meet the requisite requirements for a data center. They also come with extra features including alternate power backups and security features.

As opposed to an in-house data center, the obvious benefit of a colocation facility is that the organization does not have to spend as much money up front. Having a data center of one's own would be excessive, particularly if the business is small. Additionally, this saves the business time and resources that would have been spent on building a space that meets the criteria for a data center.

Colocation facilities, on the other hand, have disadvantages. If the colocation provider is close to the company's offices, it will save time for some employees to travel back and forth as required. When using a colocation service, monthly fees can vary greatly depending on the amount of traffic generated by the servers.

On Premise

The main difference between the on premise data infrastructure is that, as the name suggests, this system is located within the premises (e.g., building, campus, etc.). This means that the company builds their own data center from the ground up. This provides numerous advantages. 

Firstly, on premise systems are totally controlled by the company. This is excellent for companies that require micromanagement when it comes to the specifications of their data centers. Having total control over the specifications of the data center can also mean that they have complete flexibility when it comes to growth as they basically have control over all data solution decisions. 

Second, having the data center in the premises is significantly more convenient than having it off-site in a colocation service. This gives the IT staff and anyone else who would need access extreme convenience. Much time will also be saved in having an on premise data center because it rules out travel time that would have to take place when they would otherwise have to go to a colocation center. 

Unfortunately, having an on premise data center comes with significant drawbacks. With having to set everything up themselves, the company has to allot a significantly greater amount of money compared to setting up a data center through a colocation provider. The on premise data center also requires resources for building it, installing it, setting it up, and maintaining it. 

A Mix of Infrastructure

While the two types of data infrastructure systems have inherent differences, they can always be used in conjunction with each other to create a holistic network that could greatly benefit the company compared to if it had to choose between one or the other. Having different types of data infrastructures is always recommended as an organization could benefit from the advantages of both while at the same time lessening the disadvantages of either. 

For example, even if a company chooses to have an on premise data center, this does not mean that it could not benefit from a colocation service. If a company decides to have an on premise data center, they could also avail the services of a colocation provider for long term data storage. 

Data stored in the colocation service can be data that is not necessarily accessed all the time and is extremely important such as government documents, assets, intellectual property, client records, and more. 

Having these types of data stored in an off-site location is a good security feature for when the on premise data center is inoperational. Some companies heavily rely on data that loss of access to their data means loss of operations which subsequently means economic loss for them.

Since both types of systems have access to physical hardware, the two can be used in conjunction as backups of each other. The two can also be effectively used differently. For example, data storage can be delegated to one while data analysis can be delegated to the other. 

Despite their differences, the two systems have a similar end goal which is to help the company grow. Nowadays, data drives success which is why companies are turning to data centers for their scalability in the future. Having data and properly analyzing them have become a standard for today’s operations. 


While colocation services and on premise data centers have their specific differences, they can always work together and be used simultaneously to the advantage of the company. Mixed data infrastructures are highly recommended for large organizations that heavily rely on data as having data spread out on different infrastructures can increase their convenience and security at the same time. 

The decision between a colocation service and an on premise data center will have to rely on several factors such as how much the company wants to invest in a data center and what kind of data they are working with.


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