AWS vs Google Cloud vs Azure

AWS was the pioneer (2006) and maintains the largest market share (~31%). Azure grew rapidly thanks to Microsoft’s installed enterprise base (~25%). GCP, at ~11%, positions itself as the strongest option for data, machine learning and global network infrastructure.

All three invest billions annually to expand data centres, improve services and compete on price. Competition benefits the customer: prices have consistently dropped over the past decade and free tiers are increasingly generous.

For compute, all three offer virtual machines (EC2, Compute Engine, Azure VMs), managed containers (ECS/EKS, GKE, AKS) and serverless functions (Lambda, Cloud Functions, Azure Functions). GKE (Google Kubernetes Engine) is considered the most mature Kubernetes service, given that Google created Kubernetes.

For databases, AWS offers the greatest variety (RDS, DynamoDB, Aurora, Redshift). GCP stands out with BigQuery for analytics and Spanner for globally distributed databases. Azure integrates naturally with SQL Server and Cosmos DB. For storage, all three offer equivalent object storage (S3, Cloud Storage, Blob Storage) at similar prices.

All three charge per usage (pay per second or hour of compute, GB stored, GB transferred). Compute prices are similar, with 5–15% differences depending on instance type and region. Egress traffic is a significant cost across all three, with GCP offering slightly more competitive prices.

To save money, all three offer commitment discounts: Reserved Instances (AWS), Committed Use Discounts (GCP) and Reserved VM Instances (Azure), with savings of 30–70% over on-demand prices. AWS and GCP also offer spot/preemptible instances with discounts up to 90% for interrupt-tolerant workloads.

AWS stands out for its breadth of services (over 200), ecosystem maturity and the largest community of certified professionals. If you need a specific cloud service, AWS very likely offers it. Documentation is extensive, though it can be overwhelming.

GCP shines in data and machine learning (BigQuery, Vertex AI, TensorFlow), Kubernetes (GKE) and the global Google network (the same infrastructure used by Google Search and YouTube). Its console is considered the most intuitive of the three. Azure is the natural choice for companies already using Microsoft 365, Active Directory, .NET or SQL Server. Microsoft ecosystem integration is its greatest competitive advantage.

The CLI and SDKs from all three providers are mature. AWS has the most complete CLI (aws cli), GCP offers gcloud with a more coherent experience, and Azure has az cli plus native Visual Studio integration. All three support IaC (Infrastructure as Code) with Terraform, in addition to their own systems (CloudFormation, Deployment Manager, ARM/Bicep).

For support, all three offer plans from basic (free) to enterprise (thousands of dollars per month with response SLA). For startups, AWS Activate, Google for Startups and Microsoft for Startups offer significant free credits (between $5,000 and $100,000 depending on the programme).

If your team already masters one provider, the cost of switching is rarely justified. If starting from scratch: choose AWS if you need the widest variety of services, GCP if your focus is data/ML or you need robust Kubernetes, and Azure if your organisation lives in the Microsoft ecosystem.

Many organisations opt for multi-cloud (using two providers) to avoid vendor lock-in, but this adds significant operational complexity. The pragmatic recommendation is to choose one primary provider and use specific services from another only when there is a clear advantage (for example, GCP BigQuery for analytics even though your main infrastructure is on AWS).