As cloud adoption continues to accelerate in 2025, organizations are increasingly working in multi-cloud environments or switching providers. However, navigating services across AWS (Amazon Web Services), Microsoft Azure, and Google Cloud Platform (GCP) can be confusing due to differing terminologies, features, and architectures.
This ultimate cloud service mapping guide helps you understand the equivalent services across AWS, Azure, and GCP, making it easier to compare, migrate, or build multi-cloud strategies.
☁️ Why Cloud Service Mapping Matters
Each cloud provider offers similar core services—compute, storage, databases, AI, networking—but they often use different names and APIs. Having a cloud services comparison cheat sheet is crucial for:
- Multi-cloud planning
- Workload migration
- Skill transfer across platforms
- Cost optimization and service evaluation
🔄 Cloud Service Mapping: AWS vs Azure vs GCP
Here’s a side-by-side comparison of core cloud services:
1. Compute Services
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| Virtual Machines | EC2 | Virtual Machines | Compute Engine |
| Containers | ECS / EKS / Fargate | Azure Kubernetes Service (AKS) | Google Kubernetes Engine (GKE) |
| Serverless | AWS Lambda | Azure Functions | Cloud Functions |
| Auto-scaling | EC2 Auto Scaling | Virtual Machine Scale Sets | Managed Instance Groups |
2. Storage Services
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| Object Storage | S3 | Blob Storage | Cloud Storage |
| Block Storage | EBS | Azure Disk Storage | Persistent Disks |
| File Storage | EFS | Azure Files | Filestore |
| Archival | Glacier | Azure Archive Storage | Archive Storage |
3. Databases
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| Relational DB (Managed) | RDS | Azure SQL Database | Cloud SQL |
| NoSQL Document DB | DynamoDB | Cosmos DB | Firestore |
| In-memory Cache | ElastiCache | Azure Cache for Redis | Memorystore |
| Data Warehousing | Redshift | Synapse Analytics | BigQuery |
4. AI & Machine Learning
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| AI Platform | SageMaker | Azure Machine Learning | Vertex AI |
| Pre-trained APIs | Rekognition, Polly, Comprehend | Azure Cognitive Services | Cloud Vision, Natural Language |
| Speech-to-Text | Amazon Transcribe | Azure Speech | Speech-to-Text |
5. Networking
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| Virtual Network | VPC | Virtual Network (VNet) | VPC |
| Load Balancing | Elastic Load Balancer | Azure Load Balancer / App Gateway | Cloud Load Balancing |
| DNS | Route 53 | Azure DNS | Cloud DNS |
| CDN | CloudFront | Azure CDN | Cloud CDN |
6. Monitoring & DevOps
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| Monitoring | CloudWatch | Azure Monitor | Cloud Monitoring |
| Logging | CloudTrail | Azure Log Analytics | Cloud Logging |
| CI/CD | CodePipeline / CodeBuild | Azure DevOps / GitHub Actions | Cloud Build / Cloud Deploy |
| IaC | CloudFormation | ARM Templates / Bicep | Deployment Manager / Terraform |
7. Identity & Access Management
| Service Type | AWS | Azure | Google Cloud |
|---|---|---|---|
| IAM | AWS IAM | Azure Active Directory (Entra ID) | IAM |
| SSO & Federation | Cognito / IAM Federation | Entra ID | Identity Platform |
| Policy Management | IAM Policies | Role-Based Access Control (RBAC) | IAM Policies |
📈 Key Insights for 2025
- AWS continues to lead in breadth of services and global infrastructure.
- Azure excels in enterprise integration, especially for Microsoft-based workloads.
- GCP stands out for data analytics, AI/ML capabilities, and developer-friendly tools.
- Cloud-native services such as serverless computing, Kubernetes, and AI APIs are becoming the default for modern workloads.
- Multi-cloud strategies are driving the need for portable architecture and service parity.
✅ Choosing the Right Provider: What to Consider
When comparing services across clouds, evaluate:
- Your team’s familiarity with platforms
- Application architecture and dependencies
- Compliance and data sovereignty
- Pricing models (e.g., sustained use vs reserved vs pay-as-you-go)
- Integration needs with existing systems (e.g., Microsoft 365, AWS S3)
📌 Conclusion
Understanding the service equivalence between AWS, Azure, and GCP empowers businesses to make informed cloud decisions. Whether you’re migrating, going multi-cloud, or simply comparing features, having a service mapping reference like this helps reduce friction and accelerate your cloud strategy.
Keep this guide bookmarked as a quick-reference cloud comparison sheet as you architect your next-gen infrastructure in 2025 and beyond.
🔍 SEO Meta Title:
The Ultimate Cloud Service Mapping Between AWS, Azure, and GCP (2025 Guide)
📄 SEO Meta Description:
Compare AWS, Azure, and GCP services side by side. This 2025 cloud mapping guide breaks down compute, storage, databases, AI, and more for smarter cloud decisions.