
Cloud Platforms Comparison: AWS vs Azure vs GCP
A Beginner’s Roadmap
Introduction
In today’s digital era, cloud computing has changed the game. As a technology trainer at Amypo Technologies, I guide beginners through the three major platforms—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)—each of which offers unique capabilities suited to different use cases and industries.
Image Insights
• Core Service Comparison – A clear visual breakdown showing compute, storage, and networking across AWS, Azure, and GCP.
• Strengths & Weaknesses – A colourful table summarizing the pros and cons of each platform.
• Service Range Overview – Infographic comparing service catalogs, use cases, and pricing highlights.
AWS (Amazon Web Services)
• Launched in 2006.
• Market leader with ~31% market share.
• Offers 200+ services, unmatched in maturity and global reliability.
Microsoft Azure
• Second in market share with ~25%.
• Excels in the Microsoft ecosystem.
• Strong hybrid-cloud solutions and enterprise appeal, enhanced by AI tools like Copilot.
Google Cloud Platform (GCP)
• Around 10% market share shines in AI/ML, containers, and analytics.
• Built on Google’s global infrastructure with tools like BigQuery and GKE.
1. Compute
• AWS: EC2, Elastic Beanstalk, ECS/EKS, Lambda – the broadest range.
• Azure: Virtual Machines, App Service, AKS, Functions – seamless MS integration.
• GCP: Compute Engine, App Engine, GKE, Cloud Functions – cost-efficient and container-focused.
2. Storage
• Object: S3 / Blob Storage / Cloud Storage
• Block: EBS / Managed Disks / Persistent Disk
• Cold: Glacier / Archive Blob / Coldline
3. Databases
• Relational: RDS / Azure SQL / Cloud SQL
• NoSQL: DynamoDB / Cosmos DB / Datastore
• Analytics: Redshift / Synapse / BigQuery
4. Networking
• Each platform provides VPCs, PMCs, Load Balancers, and CDN, with differences in implementation across AWS, Azure, and GCP.
5. DevOps & Containers
• AWS: CodePipeline, CodeBuild, EKS/ECS
• Azure: Azure DevOps, AKS
• GCP: Cloud Build, GKE
6. AI / ML / Analytics
• AWS: SageMaker, Rekognition
• Azure: Cognitive Services, Synapse, Copilot
• GCP: Vertex AI, BigQuery
Pricing Snapshot
• AWS: Extensive services, but billing can be complex
• Azure: Competitive, especially for Microsoft customers; strong ARM/Spot offerings
• GCP: Best for large data, big discounts on sustained usage, and preemptibles
Industry Use Cases
• Enterprise IT: Azure integrates with Active Directory and Windows Server.
• Startups: AWS for its vast services; GCP for container-native, cost-effective scaling.
• Data & AI: GCP is ideal for analytics; AWS/Azure close behind with strong ML offerings.
• Hybrid Cloud: Azure excels; AWS/Azure hybrid supported through multi-cloud tools
Beginner’s Roadmap
• Define Your Goal – Web app? Data pipeline? Explore providers aligned with your needs.
• Learn the Core Services – VM, storage, databases, and networking basics.
• Earn a Certificate – AWS/Azure certs are in demand
• Build Projects – Deploy a static site, containerize an app, and analyze with BigQuery.
• Master Cost Optimization – Explore reserved, spot, and ARM instance strategies
• Expand to DevOps & AI – Explore CI/CD pipelines and AI models with built‑in services.
Conclusion
• AWS = maturity & breadth—perfect for diverse needs.
• Azure = seamless enterprise and hybrid integration, plus AI advantage.
• GCP = excellent for containers, analytics, and cost efficiency.
Your choice depends on:
✅ Cloud maturity and feature depth
✅ Pricing and enterprise alignment
✅ Learning curve and community support
✅ Your project goals and budget
Ready to explore the cloud? At Amypo Technologies Pvt Ltd, we support beginners and teams across Coimbatore in mastering AWS, Azure, and GCP. Reach out to start your journey to cloud proficiency!
You’re welcome to share and discuss—let’s build cloud skills together! For further details on choosing cloud platform, reach us!