AWS vs GCP: Which Cloud Provider?
AWS is the broadest, most mature cloud with the largest service catalog; GCP is a strong challenger with leading data, ML, and Kubernetes tooling.
AWS has the widest range of services, the deepest regional footprint, and the largest ecosystem of integrations and talent, making it a safe default for almost any workload. GCP differentiates on data analytics (BigQuery), managed Kubernetes (GKE invented much of the space), and developer ergonomics, often with simpler pricing. AWS wins on breadth and maturity; GCP wins on data, Kubernetes, and clean defaults.
| AWS | GCP | |
|---|---|---|
| Breadth | Largest catalog | Focused, growing |
| Strengths | Everything, maturity | Data, ML, Kubernetes |
| Pricing | Granular, complex | Simpler, sustained-use |
| Ecosystem | Largest | Strong, smaller |
| Best for | Broad, mature workloads | Data/ML, GKE-first teams |
Use case and ecosystem
AWS suits teams wanting the widest service selection, the most regions, and the biggest hiring pool. GCP suits data-heavy and ML workloads, teams standardizing on Kubernetes, and those who value BigQuery and simpler sustained-use discounts. Both have mature managed databases, serverless, and networking.
In CI and deploy
Both have first-class GitHub Actions support via OIDC, so you deploy without long-lived keys. Either deploys cleanly from managed runners, where faster runners shorten container builds, Terraform plans, and deploy steps.
The verdict
Want the broadest catalog, deepest maturity, and largest talent pool: AWS. Want best-in-class data analytics, ML, and Kubernetes with simpler pricing: GCP. Many teams default to AWS and reach for GCP specifically for BigQuery, ML, or a GKE-centric platform.