AWS vs Google Cloud: Breadth Against Depth

AWS has more of everything. Google Cloud is better at a few specific things. Whether that trade favours you depends almost entirely on your data workload.

30 March 2026 3 min read

AWS is the larger platform by every measure — services, regions, market share, third-party tooling. Google Cloud is smaller and does not try to match it item for item. It concentrates on a narrower set of things and is genuinely ahead on some of them.

The clearest dividing line: data

If your organisation’s centre of gravity is analytics, BigQuery is the strongest single argument either platform makes. It is serverless in a way Redshift is not: no cluster to provision, no node type to choose, no resize window. You load data and write SQL.

AWS answers with Redshift Serverless, Athena over S3, and EMR, and those are capable. But the ergonomics of BigQuery — particularly for teams without a dedicated data platform engineer — remain ahead. If a large part of your value comes from querying large datasets, this alone can decide the platform.

Kubernetes

Kubernetes originated at Google, and GKE reflects it. Autopilot mode in particular removes node management entirely: you deploy pods and pay for what they request, with Google handling the nodes underneath.

EKS has improved substantially and, with managed node groups and Fargate, is a reasonable experience. It still involves more assembly. For a team that wants Kubernetes without becoming Kubernetes operators, GKE is the easier road.

Networking

Google runs a global private backbone and its VPCs are global objects with regional subnets, so a single VPC can span regions without peering. On AWS a VPC is regional, and connecting regions means peering or Transit Gateway.

For a multi-region architecture this simplifies GCP designs noticeably. For a single-region deployment it makes no practical difference.

Where AWS is clearly ahead

Service breadth — if you need a specific managed service, AWS is more likely to have it.
Regions and availability zones — a wider footprint, particularly outside North America and Europe.
Ecosystem — more third-party integrations, more Terraform coverage, more Stack Overflow answers, more people who have hit your exact error.
Marketplace — a far larger catalogue of vendor software billed through your cloud account.
Enterprise procurement — more organisations already have an AWS agreement, which is a real advantage in large companies.

Pricing behaviour

	AWS	Google Cloud
Automatic discounts	None	Sustained use discounts apply automatically
Commitment discounts	Reserved Instances, Savings Plans	Committed use discounts
Per-second billing	Yes on most instances	Yes
Scale to zero	Lambda, Fargate Spot	Cloud Run, a stronger default story
Egress	Per GB after free tier	Per GB after free tier, similar order
Analytics billing	Redshift cluster or serverless RPU	BigQuery bytes scanned or slots

Sustained use discounts are a genuine convenience: on GCP a long-running instance gets cheaper without you doing anything. On AWS the equivalent saving requires actively buying a commitment.

Operational complexity

AWS gives you more knobs. That is a strength when you need them and a cost when you do not. IAM policy documents, VPC design, security group versus NACL, and the sheer number of ways to run a container all take time to learn.

GCP has fewer choices at each step, and its defaults are more often the right ones for a small team. The flip side is that when you need something unusual, GCP is more likely not to have it.

Common questions

Is Google Cloud cheaper than AWS?

For comparable instances, broadly similar. GCP’s automatic sustained use discounts help long-running workloads without effort, and Cloud Run is very cheap for low-traffic services. For heavy egress or analytics the answer depends entirely on your query and traffic patterns.

Is GCP a risk because Google discontinues products?

The reputation comes from consumer products. Core GCP services have deprecation policies with long notice periods, and the enterprise offering has been stable. It is worth checking the specific service you plan to depend on.

Can I use BigQuery without moving everything to GCP?

Yes. BigQuery Omni can query data in other clouds, and plenty of teams run compute on AWS and analytics on GCP. It adds a data transfer cost and a second platform to operate, so make sure the analytics advantage justifies it.

Which has better AI infrastructure?

Both are strong. GCP has TPUs and Vertex AI with tight integration; AWS has the widest GPU instance selection and Bedrock for managed model access. Choose on the specific models and hardware you need.

Where to go next

Platform guides: AWS and Google Cloud. Account configurations are on the AWS and Google Cloud pages.

AWS Google Cloud