Any of the three will run almost anything. The interesting question is not capability, it is fit: what each platform makes easy, what it quietly makes expensive, and what it assumes you already have. Here is the honest version.
AWS: the widest catalogue, and the cost of that width
AWS has the largest service catalogue, the longest track record, the most third-party tooling and the deepest pool of engineers who have used it. Whatever you are trying to do, someone has done it on AWS and written it up.
The cost of that breadth is cognitive. There are usually several services that could solve your problem, with overlapping remits and different pricing models, and choosing badly is easy. Identity and access management is powerful and unforgiving. Networking is explicit — which is a virtue at scale and a tax on a small project.
Choose it when you want maximum optionality, you are hiring for existing skills, or you need a specific managed service that only AWS has.
Google Cloud: strongest where data is the point
Google Cloud is the platform people migrate to for analytics rather than away from. Its data warehouse is genuinely differentiated: serverless in a way competitors approximate, and pleasant to use. Its Kubernetes service is widely regarded as the most polished, which is unsurprising given where Kubernetes came from. The networking, built on Google’s own backbone, is excellent.
The catalogue is narrower than AWS’s, and the ecosystem of third-party integrations is smaller. For a conventional three-tier web application, the advantage over the other two is modest.
Choose it when the centre of gravity is data, analytics or machine learning, or when you are heavily invested in Kubernetes.
Azure: the enterprise gravity well
Azure‘s decisive advantage is rarely technical. If an organisation already runs Active Directory, Microsoft 365 and Windows Server, Azure integrates with all of it natively, the licensing arrangements are favourable, and identity is one system instead of two. That is a large, real advantage that has nothing to do with instance pricing.
It is also the strongest hybrid story of the three, which matters when part of the estate is staying on-premises indefinitely. Outside the Microsoft ecosystem, the technical case is more even.
Choose it when the organisation is already Microsoft-centric, when Windows workloads are involved, or when hybrid is a requirement rather than a phase.
Where they behave alike
Three things are true of all of them, and are worth internalising before picking any:
- Egress is the expensive part. Compute pricing is broadly competitive. Data transfer out is where consumption bills surprise people, and it is the line item to model before committing.
- The managed services are the lock-in. A virtual machine is portable. A proprietary queue, a proprietary function runtime and a proprietary identity model are not. Adopt them deliberately, knowing what you are trading.
- The default is not the cheap option. All three reward committed-use discounts and reserved capacity substantially. On-demand list price is the worst price any of them offer.
And when none of them is the answer
The comparison is usually framed as a three-way choice, which quietly assumes you need a hyperscaler. Frequently you do not. If the workload is a handful of Linux servers and a database, a flat-rate provider — Hetzner, Linode, DigitalOcean, UpCloud — will do it for a predictable monthly figure and considerably less operational surface area.
The honest heuristic: pick a hyperscaler when you intend to consume the platform, not merely to run servers on it. If your architecture diagram is mostly virtual machines, you are paying for breadth you will not use.
See how to choose a cloud provider for the framework, and put specific configurations side by side once the field is narrow.