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DATABASE & INFRASTRUCTURE
AWS (Amazon Web Services) vs Google Cloud AI
AWS for a broader ecosystem and SageMaker; Google Cloud for Vertex AI and Gemini integration.
Pros and Cons
AWS (Amazon Web Services)
Strengths
- Cloud market leader with the broadest ecosystem
- SageMaker for end-to-end ML
- Bedrock for multi-LLM API access
- Pre-built AI services: Textract, Comprehend, Rekognition
- More local partners and consultants
Limitations
- Complex pricing that's hard to predict
- Proprietary AI models less competitive
- Steep learning curve
Google Cloud AI
Strengths
- Vertex AI: unified ML platform
- Access to Gemini and cutting-edge Google models
- BigQuery for large-volume analytics
- More transparent AI services pricing
- Integration with Google Workspace
Limitations
- Smaller market share than AWS
- Fewer specialized local partners
- Some services less mature than AWS
Which to choose?
AWS for businesses seeking the most complete cloud ecosystem. Google Cloud for those wanting the best AI models and already using Google.
Our verdict
For SMEs approaching cloud AI, the choice is often driven by the existing ecosystem. AWS is the safe bet with the broadest portfolio of services. Google Cloud excels in AI with Vertex AI and Gemini. In practice, many SMEs need neither: Anthropic or OpenAI APIs + Supabase + Vercel cover most AI use cases at much lower costs.
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