Beyond latency: Why population density drives edge computing ROI

While this adage has applied to property values and their overall desirability in traditional, brick-and-mortar real estate markets for generations, this saying can also be used to define success for the next generation of data centers operating at the edge. 

To put it another way, where home and commercial real estate markets tend to focus on geography, edge data centers must now carefully factor population proximity into their decisions where to locate, as this will affect latency times. Making the right choices gives data center operators the best chance to deliver fast, reliable, and always-available digital experiences their customers and their end users demand. 

Edge growth demands new strategies

This shift in thinking is a response to an edge computing industry that now finds itself at a critical inflection point that may require new variables in strategic decision-making. 

Recent estimates project that the total global revenue of the edge computing market will increase nearly tenfold in just seven years – from $16.45 billion in 2023 to $155.9 billion by 2030. Additional research shows that 75% of new data is expected to be created outside of central data centers by the end of 2025. 

Both of these findings point to a new dynamic: the fact that the edge computing industry now faces new considerations that outweigh latency metrics and other variables used in the past.

Why hyperscalers’ economics create population proximity gaps

While companies providing digital services have long obsessed over geographic coverage and millisecond improvements, forward-thinking enterprises are now recognizing that population density – not just proximity – represents the true determining factor in their edge infrastructure ROI and overall success.

Hyperscalers face a fundamental economic challenge when it comes to population-dense markets. Their business model depends on massive scale to achieve cost efficiencies, requiring enormous facilities with substantial land footprints and power capacities. In population-dense urban areas, land costs, power infrastructure expenses, and regulatory complexity make these large-scale deployments cost-prohibitive.

This economic reality drives hyperscalers to build their major infrastructure in lower-cost rural or suburban locations where they can achieve the scale economies their model requires. While AWS, Microsoft, and Google could theoretically build in downtown areas, the cost structure doesn’t align with their massive infrastructure requirements and margin expectations.

For edge services specifically, hyperscalers typically rely on virtualized solutions and distributed computing zones that leverage existing telecommunications infrastructure or partner facilities. These software-defined edges – like AWS Wavelength zones, Microsoft Azure Edge Zones, and Google Distributed Cloud Edge – offer broad geographic reach but with limited physical presence in the most population-dense areas where latency matters most.

The colocation advantage: Multi-tenant economics enable population proximity

Colocation data centers solve the population proximity challenge through a fundamentally different economic model. While hyperscalers require massive scale at individual locations to justify their infrastructure investments, colocation providers achieve the necessary scale through multi-tenancy. In doing so, they can successfully spread the cost of population-dense real estate across multiple customers sharing the same facility.  

This multi-tenant approach makes the economics work in expensive urban markets where hyperscalers can’t justify dedicated facilities. By serving dozens of customers from a single strategically located data center, colocation providers can absorb the higher costs of prime real estate, power infrastructure, and regulatory compliance that come with being close to major population centers. 

The colocation model can deliver better population reach through dedicated physical infrastructure that is positioned where customers need it most. For example, DataBank’s data centers are within a 50-mile radius of 50% of the population in the United States and 100 miles from 60%. This positioning is economically viable because the infrastructure costs are shared across multiple tenants, where each accesses dedicated resources within the same facility.

When a colocation facility positions itself within optimal distance of major population centers, it provides the dedicated processing power, storage, and connectivity that more population-dense applications demand. Unlike hyperscaler edge zones that share resources across larger geographic regions, colocation facilities can dedicate specific capacity to individual customers while maintaining multi-tenant economics that make the location strategy more sustainable. 

Most importantly, colocation providers can respond to population growth opportunities through this scalable economic model. As demographics shift and new urban centers emerge, colocation companies can deploy facilities in these markets by leveraging multi-tenancy to justify the higher costs. This approach allows them to capture population proximity advantages through shared infrastructure economics. 

Positioning for edge computing’s explosive growth

As the edge computing market grows from $16 billion to $155 billion by 2030, success will belong to those who understand that location truly is everything. Hyperscalers may offer broad geographic coverage, but colocation providers deliver what matters more: infrastructure strategically positioned within optimal reach of the population clusters that drive tomorrow’s digital economy.

About the author

Joe Minarik joined DataBank as Chief Operations Officer in January 2022, overseeing all data center operations, engineering, construction, managed services, and IT operations. He brings extensive cloud and data center expertise from his 16-year tenure at Amazon, where he led infrastructure development and served as Global Head of Data Center Supply. Prior to Amazon, Minarik held senior IT positions at Disney and Napster, and holds a B.S. in Computer Science from the University of Michigan.

Article Topics

colocation  |  data centers  |  Databank  |  digital infrastructure  |  edge computing  |  EDGE Data Centers