Cloud providers compete on hundreds of services, but most developers use the same 5-10. This comparison focuses on what actually matters for side projects and early-stage startups: free tiers, serverless deployment, and developer experience — not enterprise sales features.
Quick Comparison
| AWS | Azure | GCP | |
|---|---|---|---|
| Market share | ~32% (#1) | ~23% (#2) | ~11% (#3) |
| Free tier | 12 months (limited) + Always Free | 12 months + Always Free | Always Free (most generous) |
| Serverless compute | Lambda | Functions | Cloud Functions + Cloud Run |
| Kubernetes | EKS | AKS | GKE (best managed K8s) |
| Database | RDS, DynamoDB, Aurora | SQL Database, Cosmos DB | Cloud SQL, Firestore, Spanner |
| AI/ML services | SageMaker, Bedrock | Azure AI, OpenAI Service | Vertex AI, Gemini API |
| Deploy UX | Complex (many services) | Moderate (Portal-based) | Best (Cloud Run is magic) |
| CLI experience | awscli (verbose) | az (verbose) | gcloud (best CLI) |
| Pricing model | Pay-per-use (complex) | Pay-per-use | Pay-per-use (simplest) |
AWS — The Everything Store of Cloud
AWS has the most services (200+) and the largest market share. For any use case, AWS has a service for it — probably three. The downside is complexity: the console is overwhelming, IAM is infamously confusing, and cost management requires active monitoring.
Strengths: Most services and features. Widest global infrastructure (105+ availability zones). Lambda pioneered serverless. S3 is the universal storage API. Bedrock for managed LLMs. DynamoDB for serverless NoSQL. Largest job market for cloud skills.
Weaknesses: Console UX is overwhelming. IAM permissions are complex and error-prone. Cost unpredictability (stories of surprise bills are common). Free tier is limited (many services not included). AWS support is expensive. More verbose than GCP or Azure for simple tasks.
Best for: Teams that need maximum service selection, large-scale applications, companies heavily invested in the AWS ecosystem, developers who want the most widely marketable cloud skills.
Azure — Best for Microsoft Shops and AI
Azure is the natural choice for .NET, C#, and enterprise Microsoft environments. Its killer advantage in 2026: exclusive OpenAI Service (GPT-4, DALL-E on Azure infrastructure). For AI-first startups, this alone can justify Azure.
Strengths: Deep Microsoft integration (Active Directory, .NET, SQL Server, GitHub). Exclusive OpenAI Service (GPT models on Azure). Good hybrid cloud capabilities. Visual Studio/Azure DevOps integration. Strong enterprise compliance certifications. Good for Windows-based workloads.
Weaknesses: Console is slow and inconsistent. Documentation quality varies wildly. Some services feel less polished than AWS/GCP equivalents. Free tier is stingier than GCP. More outages historically than AWS or GCP.
Best for: .NET/C# teams, Microsoft enterprise environments, AI startups that want Azure OpenAI Service, companies using Active Directory and Microsoft 365.
GCP — Best Developer Experience
Google Cloud has the best developer experience by a clear margin. Cloud Run (serverless containers) is magical — push a container, get a URL, pay zero when idle. BigQuery is unmatched for analytics. The gcloud CLI is the best of the three. Free tier is genuinely generous.
Strengths: Cloud Run is the best serverless deployment experience. GKE is the best managed Kubernetes. BigQuery is unmatched for data analytics. Generous Always Free tier. Best CLI (gcloud). Firebase integration for mobile/web apps. Vertex AI + Gemini API for AI workloads.
Weaknesses: Smallest market share (fewer community resources). Fewer availability zones than AWS. Can feel like Google has less commitment to cloud (vs AWS's core business). Enterprise support is less mature. Fewer managed database options than AWS.
Best for: Developers who value great UX, Kubernetes workloads (GKE), data-heavy applications (BigQuery), Firebase users, projects that want the simplest serverless deployment (Cloud Run).
Which Cloud for Side Projects?
| Scenario | Best Cloud |
|---|---|
| Static site / frontend | Vercel/Netlify/Cloudflare (skip cloud) |
| Serverless API + database | GCP Cloud Run + Supabase |
| AI-first application | Azure (OpenAI Service) or GCP (Gemini) |
| Maximum free tier | GCP Always Free |
| .NET / C# / Microsoft stack | Azure |
| Maximum services, large scale | AWS |
Bottom line: For most side projects, you don't need AWS/Azure/GCP — Vercel + Supabase covers 90% of use cases. If you need cloud: GCP for the best developer experience, AWS for maximum capabilities, Azure for Microsoft shops and OpenAI access. See our hosting comparison and backend comparison for lighter alternatives.