The Cloud Wars Continue
After helping 200+ businesses migrate to the cloud over the past five years, we've developed strong opinions about when to use each platform. Here's our honest take.
Quick Comparison
| Feature | AWS | Azure | GCP |
|---|---|---|---|
| Market Share | 32% | 23% | 11% |
| Best For | Enterprise, Startups | Microsoft Shops | AI/ML, Data |
| Learning Curve | Steep | Moderate | Moderate |
| Pricing | Complex | Complex | Simpler |
Amazon Web Services (AWS)
Strengths
- **Most mature ecosystem**: 200+ services for virtually any use case
- **Global infrastructure**: 33 regions, 105 availability zones
- **Startup friendly**: Generous free tier and startup credits
- **Innovation leader**: First to market with most services
Weaknesses
- Overwhelming number of choices
- Complex pricing that requires expertise
- Support costs can be high
Best For
Startups seeking scalability, enterprises needing specific services, companies building complex architectures.
Microsoft Azure
Strengths
- **Microsoft integration**: Seamless with M365, Dynamics, Windows Server
- **Hybrid cloud leader**: Best Azure Arc and Azure Stack options
- **Enterprise agreements**: Leverage existing Microsoft licensing
- **AI Copilot integration**: Built into every service
Weaknesses
- Some services feel like afterthoughts
- Portal can be confusing
- Documentation gaps
Best For
Microsoft-centric organizations, enterprises with existing EA agreements, hybrid cloud needs.
Google Cloud Platform (GCP)
Strengths
- **AI/ML leadership**: Best-in-class Vertex AI and BigQuery
- **Data analytics**: Unmatched for large-scale data processing
- **Container expertise**: Kubernetes was born here
- **Network performance**: Google's global network
Weaknesses
- Smaller service catalog
- Fewer enterprise features
- Smaller partner ecosystem
Best For
Data-driven companies, AI/ML workloads, containerized applications.
Our Recommendation
For most SMBs, we recommend:
- **Microsoft shops**: Azure (especially with M365)
- **Startups**: AWS (credits, scalability, ecosystem)
- **Data companies**: GCP (analytics, AI/ML)
The Multi-Cloud Reality
Increasingly, our clients use multiple clouds:
- Azure for productivity (M365)
- AWS for production workloads
- GCP for analytics
This approach maximizes strengths while avoiding vendor lock-in.
Ready to migrate to the cloud? Let's discuss your options.