In short: comparing AWS vs Azure vs Google Cloud on feature lists is a waste of time — all three can run almost anything. Choose on four practical axes instead: what your team already knows, your data transfer volume, your existing enterprise agreements, and how hard it would be to leave. Egress pricing and exit terms matter more to most organizations than any capability difference.
Every AWS vs Azure vs Google Cloud comparison eventually becomes a table of thousands of services, which tells you nothing useful. The three platforms converged years ago on the capabilities most teams need. The differences that remain are commercial and organizational.
How we compared
This is a selection framework, not a benchmark. RankBoast has not run comparative performance testing across these platforms and publishes no such figures — see our review methodology. Prices and terms come from each provider’s published documentation and change frequently.
The real difference is not capability
In AWS vs Azure vs Google Cloud, all three offer compute, managed databases, object storage, serverless functions, managed Kubernetes, queues and identity. For the overwhelming majority of workloads, the question is not whether a platform can do it but what it costs and who on your team can operate it confidently at 3am.
That reframes AWS vs Azure vs Google Cloud from a technical comparison to four questions with answers specific to your organization.
AWS vs Azure vs Google Cloud: the four axes that decide it
| Axis | Why it dominates |
|---|---|
| Existing skills | The platform your team already knows will be cheaper to run and safer to operate, regardless of which is theoretically better. |
| Data transfer volume | Egress is billed per gigabyte and is the cost most often underestimated. Model it before choosing. |
| Existing agreements | Enterprise licensing and committed-spend discounts can move effective pricing more than list prices differ. |
| Exit cost | How much work and money is it to leave? Managed services are the stickiest part, not compute. |
Egress: the line item that decides bills
Storing data is cheap; moving it out is not. AWS publishes 100GB per month of free data transfer out, aggregated across services and regions, with per-gigabyte charges beyond that. For a data-heavy or media-serving workload, that becomes a dominant cost long before compute does.
This is where alternatives outside the big three deserve consideration. Cloudflare R2, for example, publishes storage at $0.015 per GB-month with no egress charges at all, and a free tier of 10GB storage with unlimited egress. For a workload whose cost is dominated by serving data out, that structural difference outweighs feature comparisons entirely — the subject of our R2 versus S3 comparison.
Model your egress in gigabytes per month before you compare anything else. It is the single most clarifying number in the decision.
Lock-in has genuinely eased on one axis
Exit cost used to include a punitive data transfer bill. That has changed: AWS now states it offers eligible customers free data transfer out to the internet when they move all of their data off AWS, or all of their data off a particular service.
Read that carefully, because the conditions matter — it applies to moving all data off, not to ordinary traffic. But it removes one real barrier to leaving, and it is worth knowing before you accept a lock-in argument at face value. The deeper lock-in was never the data transfer fee; it is the proprietary managed services your application is written against.
A practical selection process
- Write down what your team has operated in production. Not what they have read about.
- Estimate monthly egress in gigabytes. Include media, backups and inter-region traffic.
- Check existing enterprise agreements for committed-spend discounts already available to you.
- List the managed services you would depend on and ask what replacing each would cost. That is your true exit cost.
- Price a realistic month on two platforms using their own calculators, with your egress figure included.
If the two prices land close together, choose the one your team knows. That is not a cop-out; operational familiarity is worth more than a modest price difference.
Common mistakes
Comparing service counts. Nobody uses thousands of services. Compare the dozen you would actually use.
Ignoring egress until the first bill. The most common cloud cost shock, and entirely predictable.
Choosing on a proof of concept. A PoC tests capability, not the cost or operability of running it for three years.
Assuming multi-cloud reduces risk. It usually multiplies operational surface and skills required. Deliberate portability is different from running everything twice.
Discounting your team’s existing knowledge. It is the most valuable asset in the decision and the easiest to overlook.
Who should choose what
- Team already fluent in one platform: stay. Migration cost rarely repays a list-price difference.
- Heavy Microsoft estate and licensing: Azure usually prices better once agreements are applied.
- Data and analytics-led workloads: evaluate Google Cloud seriously on its data tooling.
- Broadest service range and hiring pool: AWS remains the default for a reason.
- Egress-dominated workload: look beyond the big three before committing. The structural pricing difference is large.
Verdict
There is no winner in AWS vs Azure vs Google Cloud, and any article claiming one is selling something. Estimate your egress, count your team’s real experience, apply the agreements you already hold, and price a realistic month on two candidates. In most organizations that process ends with the platform the team already knows — which is the correct answer, arrived at properly.
What we would need to test to say more
A performance comparison would require identical workloads deployed across all three platforms, measured over weeks across multiple regions, with cost tracked per unit of work. We have not done that. This article compares published pricing structures and commercial terms.
Sources and methodology
Pricing and platform behavior are taken from the providers’ own published documentation, linked below and retrieved August 2026. Cloud pricing changes frequently — verify before committing. RankBoast is independent, received no payment or sponsorship from any provider named here, and holds no affiliate relationship with them. Research and drafting were AI-assisted, with each figure traced to the linked source. Errors are handled under our corrections policy.
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