Cloud vs. On-Premise Comparison: Key Differences and Similarities
Despite the phenomenal success of the cloud environments in recent decades, enterprise IT teams continue to analyze the risks and benefits of on-premise vs. cloud.
Today, organizations face the challenge of deciding whether a cloud infrastructure is a right fit for them or an on-premise environment. There are many factors that a company must consider to make this decision. To begin with, organizations need to sort their business requirements and then choose a reliable technology vendor who offers services that meet their organizational needs. In this article, we’ll look at the key similarities and differences between cloud and on-premise, which will help you decide on the best viable solution for your organization.
Table of Contents
What Is ‘On Cloud’ and ‘On-Premise’?
In recent years, the hi-tech arena has undergone significant changes in computing and communication platforms. One such prominent technological shift has been the upgrade from an on-premise infrastructure to a cloud environment. Today, cloud has become a fulcrum of most organization’s technology strategies. The computing space has seen disruptive tech changes in the past decade, with cloud taking the top spot. The value proposition offered by cloud is multidimensional. From contributing to cost savings over traditional on-premise models to providing flexibility in services, cloud has replaced traditional computing models entirely.
On cloud explained
On cloud implies hosting data, software platforms, applications and even resources on the cloud instead of in-house. This is commonly termed cloud computing, a blend of two technologies — cloud refers to networks, while computing relates to computer-related resources, applications, and services.
Enterprises pay for what they use, similar to services provided by a telecom provider. The cloud more closely associates with a subscription-based model where you only pay for what you use. Here, computing becomes a service on the cloud and customers are billed every month for utilizing these services.
Thus, cloud can be treated as a distributed collection of computing resources where applications reside anywhere on accessible networks.
On-premise explained
On-premise refers to a computing model where a company hosts everything in-house in an on-premise environment. Software, platforms, hardware, and infrastructure (communications, storage, backup, and much more), including servers and server rooms, are located within the physical confines of the organization.
On-premise and cloud computing primarily differ where resource control and infrastructure management are concerned. Traditional computer applications are hosted on local hosts on the premises, such as desktops, notebooks, and workstations.
According to IDG’s 2020 Cloud Computing Survey of over 500 IT professionals, 59% of tech buyers (involved in the purchase process for cloud computing) said they planned to be ‘mostly’ (43%) or ‘all’ (16%) on the cloud in the next 18 months.
These figures are up from 38% in 2018 who said they were mostly or all on the cloud. Around 92% said that their organization’s IT environment is at least somewhat on the cloud today, while 8% said their total IT environment is all on-premise.
According to another survey, 50 CIOs expect to see the proportion of total workload done on-premise drop from 59% in 2019 to 38% in 2021, a reduction of 41%. These figures only highlight how organizations are embracing cloud over traditional on-premise models.
Also Read: Top 10 Best Practices to Manage Hybrid Cloud Security Challenges in 2021
Key Similarities and Differences Between On-Premise vs. Cloud
The IT industry has been in transition for decades. Cloud is a one-stop solution that has received global acceptance. It simplified IT maintenance concerns by managing core infrastructure aspects over the network. Despite the various advantages, cloud deployment is not viewed as the complete answer, as some organizations still have strong preferences for on-premise solutions.
Similarities Between Cloud and On-Premise
While cloud handles infrastructure over the network, on-premise solutions deal with infrastructure at organizational premises or on-site. However, the fundamental aim of both these solutions is to reduce organizational costs and maintenance burdens by implementing agile IT infrastructure. Cloud has proven to be cost-effective and easier for small businesses, as it offers agile and flexible integrations at affordable costs. That being said, both approaches do have some similarities.
Key Similarities Between On-Premise vs. Cloud
1. Workloads within the system
Cloud is known for its ability to offer unlimited memory space, timely backup, on-demand service availability, a faster rate of application launch (and release), timely software upgrades without the need for additional hardware in case of its own data center, and the ability to handle workloads.
An on-premise infrastructure model does not offer all these services. But testing and running workloads on the cloud is a temporary solution adopted by organizations with on-premise infrastructure. Hence, as like cloud, an on-premise environment too enables cloud computing to run its workload within the system.
This allows organizations to continue their normal operations without disruption due to excess workload. Companies can test and run the additional workload on the cloud depending on the requirement.
2. A unique mix of technologies
Both on-premise and cloud infrastructure are created using a combination of technologies. This includes an operating system, a management platform, and application programming interfaces (APIs). A management platform combines a set of features or modules that enables the management of different cloud environments as well as an on-premise model.
Meanwhile, an API facilitates the development of services and applications for provisioning cloud/on-premise platforms, hardware, and software. It acts as a service gateway to enable indirect and direct cloud/on-premise software and infrastructure services to end users.
3. Additional capabilities or increased efficiencies
Virtual machines enable a greater level of customization by OS and by application needs. Packages of applications and data can vary in relation to executive, IT access, accounting, HR, marketing, sales, or even front-line needs.
As virtualization continues to grow, it’s reaching into virtually every corner of the computing network, not just in the cloud but even in on-premise networks. Virtualization provides greater advancement in terms of ease of use and customization of machines for end users. It also helps in containing costs.
Today, computing configurations have become largely complex. Some organizations find it easier to operate their networks on-premise. Here, they build ‘private clouds‘ internally and manage the workload through virtualization as observed in cloud infrastructures.
4. IT infrastructure automation
Organizations employ IT infrastructure automation to minimize manual efforts associated with managing and provisioning workloads. IT infrastructure automation aims to make all activities related to on-premise and cloud resources fast, efficient, and with minimal intervention.
IT automation frees up IT staff to address more pressing issues and architect for the future. Automating repetitive tasks is a way for IT teams to focus on important tasks that provide added value to the organization.
Owing to these advantages, IT infrastructure automation is adopted on-premise and on different cloud environments, including public, private, and hybrid clouds. It makes workload deployments far more efficient. It also helps in cutting costs, as hardware resources and software licenses are reclaimed, which would otherwise have been wasted.
Also Read: Top 10 Hybrid Cloud Solution Companies in 2021
Key Differences Between On-Premise and Cloud
As outlined above, there are a few similarities between an on-premise and a cloud environment. However, there are quite a few fundamental differences between the two. Organizations can choose one of these environments depending on their needs and the features they’re looking for in a solution.
List of Key Differences Between Cloud and On-premise
| Upfront cost
The core difference between on-premise and cloud computing models is the cost. It is also the reason for their contrasting pricing models. |
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| Deployment of resources
This refers to the difference in how the deployment of company resources is done. |
On-premise As the name suggests, resources are deployed in-house on the company’s local server in an on-premises environment. The company is solely responsible for maintaining, protecting, and integrating data on the server. |
Cloud Deployment varies according to the type of cloud computing (private, public, or hybrid). However, the critical aspect of cloud is that the deployment of data takes place on a third-party server. The advantages of this include the transfer of responsibility for security and extension space to the involved third party. In this model, the company will have all access to the cloud resources 24×7. |
| Security of data
For the security of data and compliance issues, some organizations prefer an on-premise model over the cloud. |
On-premise Extra sensitive data is preferably kept in an on-premise environment for security reasons. Confidential or critical data such as banking data or official governmental credentials cannot be shared with a third party. In such a scenario, on-premise models serve the purpose better than cloud. Some organizations prefer using on-premise models as they are more confident about keeping their data safe themselves or need to adhere to various security compliances. |
Cloud Despite cloud data being encrypted and only the provider and customer having keys to that data, most individuals and organizations tend to be skeptical over the security measures of cloud computing. Cloud has proved its mettle and obtained many security certificates over the years. But the loss of authority over the data reduces the credibility of its security claims. |
| Control of data
Companies prefer having maximum control over their data. As such, depending on their needs and model, they can choose an on-premise model or cloud. |
On-premise As seen earlier, in an on-premise model, companies keep and maintain all their data on a server and enjoy complete control of what happens to it. This allows them to enjoy superior control over their data as compared to cloud computing. Companies in highly regulated industries (e.g., banking) with extra privacy concerns are more skeptical about taking a leap into the cloud because of this reason. |
Cloud In a cloud environment, ownership of data is not transparent. Contrary to on-premise, cloud allows you to store data on a third-party server. Data and its encryption keys reside within your third-party provider. If there is significant downtime in case of an unexpected event, you would be unable to access that data. Such a computing environment is readily adopted by either those whose business is very unpredictable or the ones that do not have privacy concerns. |
| Compliance issues
Depending on compliance regulations, some companies are required to store their data on-premise and have complete control over it, while under different circumstances, other companies can choose the cloud. |
On-premise
Today, almost every company operates under some form of regulatory control, irrespective of the type of industry. Companies have to meet the compliance policies of the government that tries to protect its citizens. Compliance policies involve data protection, data sharing limits, authorship, and so on. For those organizations that need to adhere to such regulations, the on-premise model serves as a better option. Locally governed data is stored and processed under the same roof, where it is more manageable and under control. |
Cloud Cloud solutions follow specific compliance policies. However, due to the inherent nature of cloud computing involving third-party servers in its framework, some companies cannot choose a cloud model. Additionally, despite data being encrypted on the cloud, government agencies never choose this model because losing authority over their data is a clear violation of their compliance policies. |
| Flexibility & scalability of operations
Due to the ever-increasing demand and changing user requirements, modern applications are continually evolving. Flexible and scalable infrastructure ensures that user experience is not compromised. |
On-premise On-premise environments offer less flexibility because of physical servers. Running operations on-site implies resource scaling through buying and deploying new servers. Hence, scaling is a bit of a challenge under this type of model. |
Cloud The scalability that a cloud environment provides is superior to on-premise models. Here, scalability includes resizing server resources, bandwidth, and internet usage. Also, for cost-saving purposes, cloud servers are scaled down or shut down when the usage is low. This flexibility is possible due to the virtual location and resources of servers, which are managed (i.e., increased or decreased) as per convenience. Cloud resources are administered through an API gateway or an admin panel. |
| Technical involvement
An organization’s decision to choose an on-premise or cloud model depends on another critical aspect: the amount of technical involvement required. |
On-premise On-premise implies on-location physical resources as well as on-location staff that is responsible for managing the infrastructure. This model requires the complete technical involvement of a team of experts in configuring and maintaining servers. Employing a team of professionals devoted to ensuring that the infrastructure is secure and efficient can, however, be costly. |
Cloud The service provider fully manages the cloud-deployed entities. As a result, it requires minimum technical expertise from the client’s side. However, some service providers also allow a certain amount of flexibility in this context. Most importantly, outsourcing maintenance allows organizations to focus on other business-critical aspects. Yet, not all companies are willing to hand over their infrastructure and data to a service provider. |
| Energy saving
Depending on an organization’s needs and compliance issues, it can choose a cloud model over an on-premise environment to save energy. |
On-premise The energy consumption of servers is exceptionally high. Considering this factor, having an on-premise deployment will inevitably lead to more energy expenditure. A server, on average, consumes 100% of its required power. Meanwhile, an on-premise deployment demands 10-20% of that very server’s power. This acts as a maintenance burden for organizations, as they own the infrastructure and eventually end up with minimal energy savings. |
Cloud In a cloud model, however, as maintenance responsibility lies with the service provider, a lot is saved on energy requirements. The energy consumption variable comes as part of the package in a cloud deal. Simply put, organizations deploying cloud models are not burdened with energy-saving issues, as service providers use methods to deal with energy factors while renting out cloud services. Some advanced techniques, such as airflow management, are being used to address the issue of heavy power consumption in cloud environments. |
| Bandwidth enhancement
Depending on capacity requirements and future bandwidth enhancement needs, organizations need to determine if their on-premise model will suffice or whether a cloud environment would be better. |
On-premise In an on-premise infrastructure, enhancement of bandwidth and capacity relates to physically deploying new servers. However, in this model, users also enjoy better security. As one can manage things physically, you will have to make custom configurations based on organizational needs. Unlike on-premise environments, cloud fails here as an organization will only have to choose from the available options that cloud service providers (CSPs) offer. |
Cloud On the contrary, cloud gives enterprises the flexibility to upgrade their requirements, be it memory, software, server space, etc. One can make optimal use of virtual servers, virtual routers, and additional networks through cloud deployment to enhance the size and capacities of existing storage. This only demands the organization to upgrade its cloud plan. |
| Disaster recovery
Critical system failure, technical glitches, unexpected blackouts, and malware are common with any system. But how you overcome such disasters is the real challenge. |
On-premise In an on-premise model, the responsibility of security and privacy lies entirely with the organization. In case of a disaster, the infrastructure may suffer physical damage. Since the organization is solely responsible for managing its physical systems (servers, machines), restoring data from damaged hardware can pose a significant challenge. |
Cloud The cloud environment is a step ahead in this aspect as compared to the on-premises model. Cloud provides organizations instant access to virtual resources in case of any disaster. With such features, you can back up, restore, and reboot software and data in a virtual environment instantly whenever any natural or unnatural disaster hits the cloud infrastructure. |
Also Read: Top 10 Cloud Data Protection Companies in 2021
In conclusion
A cloud model employs dynamically scalable and virtualized resources as services over the internet. Cloud users rely entirely on cloud platforms for most or all infrastructure management and software execution. A cloud platform, therefore, functions as a virtual storage space.
These very foundations of cloud infrastructure are opposite to traditional on-premise computing models. In an on-premise model, all the resources are stored on local hosts, such as desktops, servers, workstations, tablets, etc., that are on the company’s premises.
Fundamentally, the two models differ in resource control and infrastructure management. While both solutions have their share of pros and cons, no one model is superior or worse than the other. Organizations can choose any one of these solutions depending on their specific needs and end objectives.
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