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

AWS leads in breadth and maturity, Azure excels in enterprise integration, and GCP leads in analytics and ML — three cloud providers compared for 2026.

At a Glance

Key Differences

• Compute: AWS EC2 offers the most instance types and configurations. Azure VMs integrate natively with Active Directory and Windows Server. GCP’s Compute Engine offers custom machine types and sustained-use discounts (automatic for running full month).
• Serverless: AWS Lambda pioneered serverless but has cold start issues. Azure Functions integrate with Microsoft ecosystem. GCP Cloud Run (serverless containers) offers the fastest cold starts and the simplest developer experience — deploy a container, get a URL.
• Kubernetes: GCP created Kubernetes (GKE) and offers the most advanced managed Kubernetes service. AWS EKS and Azure AKS have caught up but GKE still leads in features and ease of use.
• AI/ML: AWS SageMaker is the most comprehensive ML platform. Azure has deep OpenAI integration (Azure OpenAI Service). GCP’s Vertex AI and custom TPUs (Tensor Processing Units) give it the lead in training large models efficiently.
• Pricing Model: AWS and Azure charge by the hour/second with complex discount programs (Reserved Instances, Savings Plans). GCP’s sustained-use discounts are automatic — use a VM for a full month and you get a ~30% discount without committing upfront.

When to Choose AWS

Choose AWS when you need the broadest service catalog, the most mature infrastructure, and the largest community. AWS is the safest choice for most organizations — it has the most documentation, the most third-party integrations, and the most experienced engineers. AWS’s 200+ services cover every imaginable use case. If your team has AWS experience, that’s a strong reason to stay. AWS is ideal for startups scaling fast who want maximum flexibility.

When to Choose Azure

Choose Azure when your organization is Microsoft-centric — using Active Directory, Office 365, Visual Studio, or .NET. Azure’s integration with Microsoft’s ecosystem (single sign-on, licensing, billing) is unmatched. Azure has the strongest hybrid cloud story (Azure Arc) for organizations running both on-premises and cloud. Azure is the top choice for enterprise and government clients with existing Microsoft relationships.

When to Choose GCP

Choose GCP when data analytics, machine learning, or container-native infrastructure is your priority. GCP’s BigQuery is the leading cloud data warehouse. Vertex AI with TPUs is cost-effective for ML training. GCP Cloud Run offers the simplest serverless deployment. GCP’s networking (Andromeda, Jupiter) is the fastest among the three. GCP is popular with data-driven startups and organizations with deep Google integrations. At DodaTech, GCP powers the analytics pipeline for Doda Browser and DodaZIP.

Side by Side Code Example: Deploy a Serverless Function

AWS Lambda (Python)

import json

def lambda_handler(event, context):
    name = event.get("queryStringParameters", {}).get("name", "World")
    return {
        "statusCode": 200,
        "body": json.dumps({"message": f"Hello, {name}!"})
    }

Azure Functions (Python)

import azure.functions as func

def main(req: func.HttpRequest) -> func.HttpResponse:
    name = req.params.get("name", "World")
    return func.HttpResponse(
        f'{{"message": "Hello, {name}!"}}',
        mimetype="application/json"
    )

GCP Cloud Functions (Python)

def hello_world(request):
    name = request.args.get("name", "World")
    return {"message": f"Hello, {name}!"}

All three deploy a serverless HTTP function. AWS uses a specific Lambda event format. Azure uses the func.HttpRequest type. GCP’s signature is the simplest — a regular Flask-like function that returns a dictionary.

FAQ