AWS vs Azure vs GCP Service Mapping: The Complete Comparison Chart (2026)
March 10, 2026
Looking for the Azure or GCP equivalent of an AWS service? Use our comprehensive 2026 cloud service mapping chart to quickly translate your skills and architecture.
Last Updated: March 2026
The equivalent services across AWS, Azure, and GCP map directly by function: Compute (EC2 = VMs = Compute Engine), Object Storage (S3 = Blob Storage = Cloud Storage), and Serverless (Lambda = Functions = Cloud Functions). This is a cloud service mapping chart from 2026 for engineers/architects/developers porting their infrastructure and skills between the three major providers.
Master Comparison Chart
This is a table of the most common services across AWS, Azure, and GCP. There can be slight differences (e.g., Lambda has a cap of 15 minutes and Azure Functions can run for 60 minutes depending on service plan), but they have generally the same use cases.
| Category | AWS Service | Azure Service | GCP Service |
|---|---|---|---|
| Compute (VMs) | Amazon EC2 | Virtual Machines | Compute Engine |
| Serverless Functions | AWS Lambda | Azure Functions | Cloud Functions |
| Managed Kubernetes | Amazon EKS | Azure Kubernetes Service (AKS) | Google Kubernetes Engine (GKE) |
| Serverless Containers | AWS Fargate | Azure Container Apps | Cloud Run |
| Object Storage | Amazon S3 | Azure Blob Storage | Cloud Storage |
| Block Storage | Amazon EBS | Managed Disks | Persistent Disk |
| Relational Database | Amazon RDS / Aurora | SQL Database / MySQL / PostgreSQL | Cloud SQL / Cloud Spanner |
| NoSQL (Key-Value) | Amazon DynamoDB | Azure Cosmos DB | Cloud Firestore / Bigtable |
| Data Warehouse | Amazon Redshift | Azure Synapse Analytics | BigQuery |
| Virtual Network | Amazon VPC | Virtual Network (VNet) | VPC Network |
| Load Balancing | Elastic Load Balancing (ELB) | Azure Load Balancer | Cloud Load Balancing |
| Identity Management | AWS IAM | Microsoft Entra ID | Cloud IAM |
| Managed AI / ML | Amazon SageMaker | Azure Machine Learning | Vertex AI |
| Generative AI Hub | Amazon Bedrock | Azure OpenAI Service | Vertex AI (Gemini / Model Garden) |
How to Translate Your Cloud Skills
Switching clouds usually doesn't require learning new concepts, it requires learning new names and how to navigate a different portal. All major cloud providers have 99% feature parity because their customers' needs are the same: compute, storage, networking, databases, etc. Here's how to make the jump.
1. Compute & Foundations
If you know AWS EC2, you're used to AMIs (Amazon Machine Images), Instance Types, and Security Groups. In Azure, those are VM Images, VM Sizes, and Network Security Groups (NSGs). In GCP, they're Machine Families and Firewall Rules. The basic idea—renting virtual servers—stays the same.
2. Networking Topology
Networking differences are the biggest adjustment:
- AWS VPCs are regional. To connect regions, you need peering or a Transit Gateway.
- Azure VNets are also regional but can use Global VNet Peering.
- GCP VPCs are global by default. One VPC can have subnets anywhere, which feels weird if you're used to AWS's regional model. GCP has a global network, but you can still isolate resources using firewall rules and private networking.
3. Identity and Access Management (IAM)
- AWS attaches Policies to Users, Groups, or Roles.
- Azure (using Microsoft Entra ID, formerly Active Directory) uses Role-Based Access Control (RBAC) with Scopes (Management Groups, Subscriptions, Resource Groups). There are also Azure Policies-- this requires a whole separate article for a proper explanation.
- GCP uses a hierarchy: Organization -> Folder -> Project. You grant permissions to "Members" (service accounts or workspace emails) on specific resources or projects.
Transitioning Careers: A Path for Cloud Engineers
For most Cloud Engineers, "multi-cloud" doesn't mean knowing every service on every platform. It means understanding the Cloud Archetypes:
- Object Storage Expert: If you can configure bucket policies and lifecycle rules in Amazon S3, you can do the same in Google Cloud Storage in an afternoon.
- Kubernetes Native: If you manage clusters on EKS, moving to GKE or AKS is straightforward—the core Kubernetes API is the same. Only the provider-specific bits (Load Balancers, IAM) change.
- Infrastructure as Code (IaC): This is your bridge. Terraform or Pulumi let you manage all three clouds with similar logic. Learning
google_compute_instanceversusaws_instanceis easier than mastering three different web consoles.
Frequently Asked Questions (FAQ)
What is the Azure equivalent of AWS S3? The Azure equivalent of Amazon S3 is Azure Blob Storage. Both provide highly scalable and durable object storage for unstructured data.
What is the Google Cloud (GCP) equivalent of AWS EC2? The GCP equivalent of Amazon EC2 is Compute Engine. Both services allow you to launch and manage virtual machines (VMs) on a global infrastructure.
What is the AWS equivalent of Azure Functions? The AWS equivalent of Azure Functions is AWS Lambda. Both are event-driven, serverless compute services that allow you to run code without provisioning or managing servers.
What is the GCP equivalent of AWS S3? The Google Cloud equivalent of Amazon S3 is Cloud Storage. They provide similar object storage capabilities, including lifecycle management and multiple storage tiers (e.g., standard, coldline, archive).
What is the Microsoft Azure equivalent of Amazon VPC? The Azure equivalent of Amazon VPC (Virtual Private Cloud) is Azure Virtual Network (VNet). Both provide isolated network environments in the cloud where you can define subnets, IP ranges, and route tables.
Conclusion
If you're shifting your career or learning a new platform, you're not starting from zero. Check out job openings here or data on technologies and certifications here.