Hyperscale data centers meet enterprise data needs by offering scalability and high-speed processing for large volumes of data, while colocation data centers offer a different value proposition—the flexibility to rent space, utilities, and other essential resources, allowing for cost-effective expansion and management. Understanding the nuances between these two types of data centers is important for businesses looking to optimize infrastructure investments. This article provides a comparative analysis of hyperscale and colocation data centers to help you identify the best fit for your specific infrastructure requirements.
What are Hyperscale Data Centers?
Hyperscale data centers (HDCs) operate on an enormous scale to meet the processing or storage needs of the companies operating them. The word “hyperscale” describes a computer architecture’s ability to scale quickly and massively to meet increasing demand. In this context, it refers to a data center built to handle the incredible processing burdens of high tech companies.
Generally speaking, a data center with more than 5,000 servers and more than 10,000 square feet of space is considered hyperscale. Those are the minimum requirements—some HDCs hold more than a million servers. They are designed for homogenous scaling to support projects that need almost endless processing power.
The cost of building out an HDC is limiting, making them somewhat exclusive. Amazon, Google, and Microsoft all have their own hyperscale data centers. And while such companies usually build them for their own use, they may also sell services to third parties.
How do Hyperscale Data Centers Work?
Hyperscale data centers use specialized equipment, tools, and networks to process data at scale. They consist of thousands of servers working together in a distributed computing architecture. These servers operate in clusters, with each cluster responsible for a specific workload.
The software consists of load-balancing algorithms responsible for dividing the workload without overburdening any individual server. Individual servers can be used for running multiple virtual servers.
The advanced networking technologies used in hyperscale data centers include software-defined networking or network function virtualization for optimized performance by facilitating data traffic routing and flexibility in configuration.
What are Colocation Data Centers?
While some organizations host their own data centers and some pay to use the processing power of a provider’s data center, colocation data centers are a hybrid of the two. They’re essentially shared space data centers where multiple companies own and operate their own servers and network infrastructure.
The benefits are numerous. Thanks to economies of scale, they’re more affordable, and make it possible for smaller companies to build data centers at a lower cost than if they had to own, operate, and staff the entire facility. They’re scalable. They’re more reliable than what most companies could do in-house. And they make it possible for companies to take advantage of existing data centers in advantageous locations rather than going through the arduous and time-consuming process of land acquisition and build-out.
How do Colocation Data Centers Work?
Colocation data centers cater to enterprise customers by providing the opportunity for them to share data center space with other businesses. They use the same technologies as other data centers, and provide the same functionality. The difference is that more than one company’s data center operations exist in the same physical facility.
The infrastructure needed for a successful data center is considerable. Shared data centers take advantage of the economy of scale to lower the cost of providing adequate bandwidth and a cool, controlled environment for huge banks of servers.
Hyperscale Data Center Use Cases
Hyperscale data centers serve numerous different applications in different industries, depending on the organizations’ needs. Here are some of the most common.
Companies that provide data hosting and management in the form of Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) generally operate from centralized hyperscale data centers that offer sufficient power to meet the demands.
Hyperscale data centers power most of the major over-the-top (OTT) streaming platforms by providing the massive storage solutions and quick access to data they need. HDCs allow seamless transfer of data to millions of devices in parallel.
AI and Machine Learning Algorithms
Hyperscale data centers are crucial for enterprises running high-intensity artificial intelligence and machine learning (AI/ML) applications because of their capacity to handle vast data processing requirements. Google and IBM provide specialized hyperscale data centers for deep learning research and AI services, capitalizing on their high-speed connectivity and immense processing power that effectively meet the computational needs of intelligent systems.
Colocation Data Center Use Cases
Not all enterprises need the extraordinary processing power of a hyperscale data center. Here are some of the most common use cases for colocation data centers.
Performance, Control, and Cost
Because colocation is more economical than building and maintaining a private data center, businesses that need the storage capacity and processing power of a data center but cannot afford the expense or time needed to build one out are the primary market. Datacenter colocation has a 37-52 percent lower cost than building a traditional raised-floor data center. Colocating also offers extensive control over infrastructure in a way that cloud solutions do not as well as a way to minimize impact on the environment by sharing resources, reducing the strain on power and cooling utilities.
Using a colocation data center to house backup systems can provide affordable redundancy for critical data as a secondary source to in-house storage.
Companies bound by legislative or regulatory requirements to store backups off-site can meet these demands and maintain compliance by renting space in a colocation data center.
Bottom Line: Colocation vs. Hyperscale
Data centers are integral to the high performance data processing and storage needs of modern business, and colocation data centers and hyperscale data centers each address those needs differently. Colocation data centers offer control, cost-effectiveness, and sustainable infrastructure, while hyperscale centers emphasize vast processing power and scalability for applications like cloud computing and AI. The use cases for each hinge on such factors as cost, compliance, redundancy, scalability, and security, but generally speaking, colocation suits enterprises seeking affordability, control, and scalability, while hyperscale is ideal for extensive processing demands and diverse applications.
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