AWS is the broadest service catalogue in the industry. Google Cloud is the platform data teams migrate toward. This page puts the two side by side — the live configurations and prices from our catalogue, then the differences that actually decide the choice.
| In our catalogue | AWS | Google Cloud |
|---|---|---|
| Product | Buy AWS Account | Buy Google Cloud Account |
| Configurations in stock | 30 | 6 |
| Lowest price | $20 | $40 |
| Highest price | $6,500 | $75 |
| Example options | 5 VCPU / US IP · 5 VCPU / 1 Month Old / US / High Quality · 5 VCPU / 8 Months Old / UK / High Quality | $30 Deposit / USA IP · GCP Canada · GCP $300/$350 / Brazil IP |
| View options | View options |
Prices and configuration counts are read from the live catalogue. Specifications are listed exactly as supplied; nothing here is estimated.
Both are hyperscalers, so the question is ecosystem fit
AWS and Google Cloud will both run essentially any workload, and both meter it the same way. Capability is not the deciding factor — the deciding factor is which platform’s centre of gravity matches what you are building.
AWS is strongest at: AI and machine learning workloads on Bedrock, large multi-account organisations, and anything needing a managed service that only AWS offers.
Google Cloud is strongest at: Analytics pipelines, ML training and serving, and Kubernetes-first architectures.
Picking the one whose defaults already match your architecture means less configuration, cheaper support and a larger pool of people who have solved your problem before.
Where AWS is the stronger choice
Breadth. Whatever the problem is, AWS has a managed service for it, a large body of documentation, and the deepest pool of engineers who have already solved it.
Best suited to: teams who intend to consume managed services — queues, managed databases, serverless, identity — rather than just run servers.
Regions: The widest global region footprint, including multiple regions per continent, so latency and data-residency requirements can almost always be met.
Worth knowing: Data transfer out is the line item that surprises people; on-demand list price is the worst price AWS offers, so committed-use discounts matter once the baseline is stable.
Where Google Cloud is the stronger choice
Data and containers. The analytics stack is genuinely differentiated, and the managed Kubernetes offering is widely regarded as the most polished — unsurprising given where Kubernetes came from.
Best suited to: teams whose centre of gravity is analytics, machine learning or Kubernetes.
Regions: A strong global footprint built on Google’s own private backbone, which shows up as consistent inter-region latency.
Worth knowing: Credit-backed projects are attractive for evaluation, but the credit is a starting balance rather than an ongoing discount — model the post-credit run rate before committing.
The trade-offs, stated plainly
AWS: That breadth is also the cost: several services often solve the same problem with different pricing models, IAM is powerful and unforgiving, and networking is explicit in a way that is a virtue at scale and a tax on a small project.
Google Cloud: The catalogue is narrower than AWS’s and the third-party integration ecosystem is smaller, so for a conventional three-tier web application the advantage over the alternatives is modest.
How to choose between them
- Choose AWS if your workload is AI and machine learning workloads on Bedrock, large multi-account organisations, and anything needing a managed service that only AWS offers
- Choose Google Cloud if your workload is Analytics pipelines, ML training and serving, and Kubernetes-first architectures
- Choose neither if the shape of the work does not match either — the full catalogue has eight other platforms, and the comparison tool will hold four of them side by side.
Related reading
- Buy AWS Account — every AWS configuration in stock
- Buy Google Cloud Account — every Google Cloud configuration in stock
- How to choose a cloud provider — the framework behind this comparison
- How cloud billing works — why the billing model matters more than the sticker price
- Compare up to four accounts side by side
Questions
Common questions about this comparison
Is AWS cheaper than Google Cloud?
The prices in the table above are the live catalogue prices for the accounts we stock, so you can compare those directly. Running cost is a separate question and depends on the billing model: AWS bills per unit consumed and Google Cloud bills per unit consumed, which means the cheaper account is not always the cheaper month.
Can I run the same workload on both?
For ordinary Linux servers, databases and web applications, yes. The divergence starts when you adopt a platform's proprietary managed services — a specific queue, function runtime or identity model — because those are what make a migration expensive later.
Which one is better for AI and machine learning workloads on Bedrock?
That is AWS's stated strength, so it is the natural starting point. It is still worth checking region availability and the billing model against your own constraints before committing.
What do I actually get when I buy an account here?
The configuration named on the product page and nothing beyond it — the vCPU figure, region, account age or credit exactly as listed. Both product pages set out every option in stock with its own price.