In the ever-evolving landscape of information technology, the heart of digital infrastructure pulsates within data centers. These fortresses, often unseen by users but pivotal, form the backbone of our interconnected world. And the number keeps growing.
According to Statista, there are 5,375 data centers in the U.S. alone as of September 2023. This is the highest number of data centers in any country. If this is just one country, you can imagine how many data centers that exist in the entire world. It’s all because data centers have become so critical for today's technology-driven businesses. They process tons of company data in a secure, reliable environment.
So you are probably here because your organization could be at that point where it’s navigating the complex terrain of data management. In this terrain, two distinct paradigms emerge — hyperscale and colocation facilities.
We understand that within this dynamic dichotomy lies a critical decision for your organization: the choice between hyperscale and colocation, each offering its unique allure and advantages.
Journey with us as we explore the nuances that distinguish these two pillars of modern computing. First, a brief understanding of data centers.
Defining a data center
IBM defines a data center as a physical room or building that houses IT infrastructure. This includes servers, routers, storage devices, and other resources.
A data center enables businesses to build, run, and deliver applications. It also stores data for backup and compliance.
If you are thinking about moving your data center and wondering where to start, please check this guide that lays down the essentials of data center migration, as well as this that focuses on data center migration plan. We also have another vital resource for cloud migration tools.
A typical data center has six main components:
A server is a type of computer that distributes data to various end-user devices. It is essentially a specialized central processing unit (CPU).
For example, an application server contains the data that enables an app to function, e.g., user profiles, configuration settings, etc. Servers can be stacked or mounted on a rack. Each server has its own power supply, memory, storage, and other computing features.
Each server has a storage device attached to it. This is typically a hard disk drive (HDD) or a solid state drive (SDD). These devices keep the most frequently accessed data (hot data) on the server, e.g., current project files and online transactions.
Less frequently accessed data is kept in a cold storage server. Cold storage uses traditional hard drives that don't require much power or connectivity to maintain. They contain compliance data or backup data for recovery.
The networking components of a data center include routers, switches, and fiber optic cables. They maintain an internet connection between the server and the end-user devices.
4. Power supply
Since data centers must always be on, they need multiple power supplies. Data center facilities have uninterruptible power supplies (UPS) that run on batteries.
The UPS systems kick in during brief outages and protect the servers from damage. Data centers also have powerful generators that keep running during extended or severe outages.
5. Disaster recovery
In case of disruptions from natural or political events, data centers must implement strategies for disaster recovery.
For example, data centers maintain redundant servers, which are the backups of primary servers. These keep data safe in case of corruption or server failures. Redundancy servers are usually set up in a separate location from the primary servers.
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6. Climate control
Data centers need precise environmental controls to keep servers running. These include air conditioning and liquid cooling to prevent overheating.
Data centers also have specialized tools for controlling humidity, static electricity, and preventing fire.
What is a hyperscale data center?
A hyperscale data center is one that is built and owned by a major tech company. It is also known as a cloud data center.
These facilities are often located at the outskirts of big cities. For example, Google has data centers just outside of Council Bluffs, Iowa and Lenoir, North Carolina, among others.
Building a hyperscale data center is a massive financial and technological investment. For example, the cost of data center construction in Silicon Valley is $11.49 per watt. Considering that a data center uses an average of 150 watts per square foot, and additional expenses, it can cost over $1 billion to construct.
This massive cost explains why there are only a handful of companies that have their own data centers. Some of these companies include Google, Amazon, Apple, Microsoft, and Meta.
However, companies can also lease data centers from other hyperscale providers like CloudHQ. Leasing agreements last between 10 and 15 years or more, meaning they are also significant investments for businesses.
What is a colocation data center?
A colocation data center is a computing facility that rents out server space to third parties. It is built by an independent company and offers servers for small and medium businesses.
Examples of colocation providers are Equinix and Digital Reality. These companies have data centers in the Americas, Europe, Africa, Middle East, and Asia Pacific.
According to Data Center Knowledge, colocation data centers are growing in Indonesia, India, and Japan. This means that colocation data centers are gradually spreading from the U.S. and Western Europe into new markets in Asia.
Big data companies like Facebook and Amazon are also leasing colocation servers. For example, Equinix data centers host Google Cloud and AWS servers. This indicates a growing demand for computing power among the big tech players today.
Differences between hyperscale and colocation data centers
There are five key items that best illustrate the major differences between hyperscale and colocation data centers.
These items are size, price, ownership, management, and tenants.
Hyperscale data centers are massive facilities that contain millions of servers. They are ideal for businesses that generate and use huge amounts of data.
Colocation data centers, on the other hand, typically occupy a smaller footprint in terms of real estate. According to Equinix, a colocation data center occupies less than 10,000 square feet. Anything larger is considered to be hyperscale.
Hyperscale and colocation data centers offer different types of pricing options for businesses. The pricing depends on the power capacity per kilowatt. That's because servers require large amounts of electricity.
According to Energy Innovation, data centers can use over 100 megawatts of power, which is enough to support 80,000 households in the U.S.
Generally, hyperscale costs less than colocation in the short term range. For example, Digital Reality leased hyperscale at $101 per kilowatt and colocation at $243 per kilowatt in 2021. This difference is best explained by the fact that hyperscale clients typically take longer leasing periods than colocation clients. Of course the downside is that you’ll have to commit long term.
In most cases, hyperscale data centers are owned by tech giants like Amazon, Google, and Microsoft. In 2020, these three companies owned over 50% of all hyperscale data centers in the world.
Colocation data centers are owned by third party companies. They offer wholesale and retail services for their customers. Retail colocation allows businesses to rent space within the data center. This can be a section of the site, a rack of servers, or a part of a rack. Businesses that require less than 100 kilowatts of power to run their servers are considered retail customers.
Wholesale colocation is ideal for larger enterprises and government agencies that need more computing power. A wholesale colocation customer often requires more than 100 kilowatts for their servers.
Hyperscale data centers are managed by the employees of the tech giants that own them. Colocation data centers offer different management options for wholesale and retail customers.
For example, a wholesale customer may have their own technical staff overseeing the leased servers. But a retail customer may rely on the colocation staff for management.
The management options depend on the master services agreement (MSA) between the colocation provider and the individual customers.
Hyperscale data centers have one tenant. The tech company that uses it is the only one that can host its servers on the premises.
For example, Meta servers hold only Meta's data, no matter where they are located in the world.
Colocation data centers, in contrast, allow multiple tenants from a wide range of industries. For example, NTT Global offers data center leases to businesses in the following industries:
- Transportation and logistics
- Energy, etc.
Use cases for hyperscale and colocation data centers
Hyperscale and colocation data centers play a key role in supporting the following functions for organizations:
1. Streaming services
Over-the-top (OTT) streaming platforms like Netflix, Hulu, and Apple TV+ need huge storage capacities for their databases. They also require high speed internet to transfer data to millions of devices without interruption.
2. Cloud computing
Businesses that offer as-a-service solutions like Salesforce and HubSpot require data centers to host their clients' data.
For example, a software as a service (SaaS) company stores software data in a data center.
3. Artificial intelligence (AI) and machine learning (ML)
Companies venturing into AI and ML need significant computing and networking power that only big data centers can provide. However, a white paper by Schneider Electric indicates that AI workloads in data centers are increasing.
This puts a strain on current data center infrastructure. This will force hyperscale and colocation providers to adjust their capacities to meet AI demand. This means increasing resources for power, cooling, and connectivity.
4. Data backups for compliance
Certain industries like healthcare, finance, and retail must have data backups to meet regulatory obligations.
For example, the Healthcare Insurance Portability and Accountability Act (HIPAA) requires providers to keep data backups of protected health information (PHI). Institutions like hospitals can rent colocation servers for this data. Health facilities like hospitals are particularly a high level target for data compromises and theft and there has been an increase of cyber attacks on hospitals in the US.
Considerations when choosing between hyperscale and colocation data centers
According to Data Foundry, the average cost of building a data center in 2020 was $1,000 per square foot. In addition, the cost of fiber connectivity can reach well over $10,000 per mile.
Power and cooling functions are also a significant investment. With this, you need to weigh the options between building a company owned data center or leasing rack space.
Here are the main factors to consider.
1. Company size
Generally, small and medium organizations are better suited to colocation data centers. You simply lease only what you need for your operations.
Enterprise-level companies may consider wholesale colocation for more resources. Building a hyperscale data center is viable if an enterprise can fund the project and forecast a feasible return on investment.
2. Power and cooling
Retail and wholesale colocation providers often cap the power consumption for their clients. For example, some data centers allow for a maximum of one megawatt of power to maintain customer servers.
Colocation facilities also place limitations on cooling resources, which can take up 30% of power consumption. If you foresee that your organization may require more power and cooling for servers, you need to consider owning a hyperscale data center.
3. Internet connectivity
When it comes to connectivity, colocation and hyperscale data centers are quite similar. Most provide fiber optic internet at the highest speeds available today.
However, some businesses often opt for hyperscale because of the ability to switch between internet service providers (ISPs).
This level of flexibility is not possible with colocation facilities. For example, if a colocation data center uses Verizon for their internet, their customers will have to stick to that.
Hyperscale facilities only host one tenant, meaning all the staff overseeing the data servers are employees of the company that owns the data center. This means the enterprise will easily vet data center employees to meet internal standards.
With colocation facilities, customers interact with the facility's employees. This poses the risk of unauthorized access. Because of this risk, it’s important to install a cage or screen over your rented servers to serve as an extra layer of security.
Colocation is ideal for businesses with small tech teams or those with relatively low data needs. You can choose retail or wholesale pricing options that suit your budgets.
But if you are dealing with AI or supercomputing, you may find colocation more restrictive, despite the cost savings. For example, the power and cooling limitations may not fit your operations.
If this is where your organization finds itself, then it’s better to invest in a hyperscale data center.
Choosing between hyperscale and colocation is a strategic decision!
As you make the choice between hyperscale and colocation, remember that the decision is not merely technical but a strategic gateway to unlocking the full potential of data management.
This becomes even more consequential in this era of Artificial Intelligence where more computing power will be needed as companies aggressively integrate AI into workflows and services. This is a growing trend as evidenced by a recent McKinsey survey indicating that 40% of businesses plan to increase investment in AI.
How should this trend guide your choice? Go for providers that are actively integrating AI into their systems. The frontrunners are already beginning to think about powerful specialized AI chips. This will help data centers to build more efficient and flexible infrastructure.
Remember the whole essence of a data center is not only to host data and support operations. This data must always remain secure and this requires the adoption of best practices for data loss prevention.