AWS vs Azure vs GCP: Cloud Platform Comparison (2026)

In this tutorial, you'll learn about AWS vs Azure vs GCP: Cloud Platform Comparison (2026). We cover key concepts, practical examples, and best practices to help you understand and apply this topic effectively.

Amazon Web Services, Microsoft Azure, and Google Cloud Platform are the three dominant cloud providers, each with distinct strengths. This comparison covers compute, storage, networking, pricing models, and real-world use cases to help you choose the right cloud platform.

graph TD
  subgraph "Cloud Providers"
    AWS -->|1995+ services| A[Compute: EC2, Lambda]
    AWS --> B[Storage: S3, EBS]
    AWS --> C[Database: RDS, DynamoDB]

    Azure -->|200+ services| D[Compute: VMs, Functions]
    Azure --> E[Storage: Blob, Files]
    Azure --> F[Database: SQL, Cosmos DB]

    GCP -->|160+ services| G[Compute: GCE, Cloud Run]
    GCP --> H[Storage: Cloud Storage]
    GCP --> I[Database: Cloud SQL, Bigtable]
  end
  style A fill:#ff9900,color:#000
  style D fill:#0078d4,color:#fff
  style G fill:#4285f4,color:#fff

At a Glance

Compute Services Comparison

Each provider offers virtual machines, Serverless functions, and managed Kubernetes. The differences lie in performance consistency, pricing, and ease of use.

# Simulated cost comparison for a web application
# 2 vCPU, 8GB RAM, 500GB storage, 1TB egress/month

providers = {
    "AWS": {
        "compute": 32.00,     # t3.large on-demand
        "storage": 23.00,     # 500GB gp3 EBS
        "egress": 90.00,      # 1TB at $0.09/GB
        "total": 0
    },
    "Azure": {
        "compute": 28.00,     # D2s v3 on-demand
        "storage": 20.00,     # 500GB managed disk
        "egress": 87.00,      # 1TB at $0.087/GB
        "total": 0
    },
    "GCP": {
        "compute": 24.00,     # e2-standard-2 on-demand
        "storage": 20.00,     # 500GB persistent disk
        "egress": 120.00,     # 1TB at $0.12/GB
        "total": 0
    }
}

for provider, costs in providers.items():
    costs["total"] = sum(costs.values())
    print(f"{provider}: ${costs['total']:.2f}/month")
    print(f"  Compute: ${costs['compute']:.2f}")
    print(f"  Storage: ${costs['storage']:.2f}")
    print(f"  Egress:  ${costs['egress']:.2f}")
    print()

Expected output:

AWS: $145.00/month
  Compute: $32.00
  Storage: $23.00
  Egress:  $90.00

Azure: $135.00/month
  Compute: $28.00
  Storage: $20.00
  Egress:  $87.00

GCP: $164.00/month
  Compute: $24.00
  Storage: $20.00
  Egress:  $120.00

Managed Kubernetes

Google Cloud's GKE is widely considered the most mature managed Kubernetes service. AWS EKS is the most widely used. Azure AKS offers the best integration with Microsoft enterprise tools.

# Create a Kubernetes cluster on each provider

# AWS EKS
eksctl create cluster \
  --name my-cluster \
  --region us-east-1 \
  --nodegroup-name standard \
  --node-type t3.medium \
  --nodes 3 \
  --managed

# Azure AKS
az aks create \
  --resource-group my-rg \
  --name my-cluster \
  --node-count 3 \
  --node-vm-size Standard_D2s_v3 \
  --enable-managed-identity

# GCP GKE
gcloud container clusters create my-cluster \
  --zone us-central1-a \
  --num-nodes 3 \
  --machine-type e2-standard-2

Expected output:

# GKE example output
Creating cluster my-cluster in us-central1-a...done.
Cluster "my-cluster" created with 3 nodes.
Kubernetes master is running at https://<ip>:443

Serverless and Event-Driven

AWS Lambda pioneered Serverless Computing. Azure Functions integrates deeply with the Microsoft ecosystem. Cloud Run (GCP) offers the unique ability to run any container in a Serverless fashion.

// AWS Lambda — serverless function
exports.handler = async (event) => {
  const body = JSON.parse(event.body);
  const result = {
    message: `Hello ${body.name}!`,
    timestamp: Date.now(),
    provider: "AWS Lambda",
    requestId: event.requestContext.requestId
  };
  return {
    statusCode: 200,
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify(result)
  };
};

# GCP Cloud Function
import functions_framework
from datetime import datetime

@functions_framework.http
def hello(request):
    request_json = request.get_json(silent=True)
    name = request_json.get("name", "World") if request_json else "World"

    return {
        "message": f"Hello {name}!",
        "timestamp": datetime.now().isoformat(),
        "provider": "GCP Cloud Functions"
    }

Expected output (both return identical structure):

{
  "message": "Hello Alice!",
  "timestamp": "2026-06-23T12:00:00.000Z",
  "provider": "AWS Lambda"
}

Bottom Line

Choose AWS for the broadest service catalog, largest community, and most mature ecosystem — ideal for complex architectures and enterprise-scale operations. Choose Azure if your organization is invested in the Microsoft ecosystem (Active Directory, Office 365, .NET). Choose GCP for data analytics, Machine Learning, Kubernetes-first workloads, and transparent pricing with sustained-use discounts.

Practice Questions

1. Which cloud provider has the most global regions and why does that matter?
2. How does Google Cloud's pricing model differ from AWS and Azure?
3. Which provider is best suited for Kubernetes workloads and why?

FAQ

Related

• Alternatives to AWS
• Docker containers
• PostgreSQL

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