Pricing, credits, managed services, and the startup perspective
For most startups, start with a PaaS (Heroku, Railway, Render) and skip the cloud decision entirely until you need it. When you do need cloud infrastructure: choose AWS if you want the largest ecosystem and easiest DevOps hiring. Choose Google Cloud if you need strong AI/ML services or want more generous startup credits ($200K vs $100K). Our recommendation: AWS for general web applications, Google Cloud for AI-heavy products.
| AWS | Google Cloud | |
|---|---|---|
| Market Share | 31% (dominant) | 12% |
| Free Tier | 12 months + always-free tier | Always-free tier (more generous) |
| Startup Credits | Up to $100K (AWS Activate) | Up to $200K (Google for Startups) |
| Managed DB | RDS, Aurora, DynamoDB | Cloud SQL, Spanner, Firestore |
| AI/ML Services | SageMaker, Bedrock | Vertex AI, Gemini (stronger) |
| Kubernetes | EKS | GKE (better managed K8s) |
| Complexity | Higher (200+ services) | Lower (more focused) |
| Hiring Pool | Largest (most DevOps know AWS) | Growing |
Google Cloud is generally 10-20% cheaper for compute. AWS wins on reserved instance pricing. For startups, both offer credits that make the first 1-2 years effectively free.
Not initially. Use Heroku, Railway, or Render for your first year. Move to AWS/GCP when you need custom infrastructure, specific compliance requirements, or have a dedicated DevOps engineer.
Google Cloud leads with Vertex AI and Gemini integration. AWS has Bedrock (access to Claude, Llama, etc.) which is more flexible. Both are excellent for AI workloads in 2026.
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