Amazon Web Services, Microsoft Azure and Google Cloud Platform together run a large share of the world's cloud workloads, and all three can host almost anything a business needs. That makes the AWS vs Azure vs Google Cloud question less about which is "best" and more about which fits your existing software, your team's skills and the specific services you rely on. This guide compares them on the factors that actually change outcomes, and deliberately avoids price lists, which change too often to be useful in an article.
What the three have in common
Before looking at differences, it helps to know how much is the same. All three offer:
- Virtual machines in many sizes, including GPU instances for AI and machine learning work.
- Managed relational databases (MySQL, PostgreSQL, SQL Server) and NoSQL options.
- Object storage with multiple storage classes for hot and archive data.
- Managed Kubernetes, serverless functions, load balancers, CDN and DNS.
- Regions in India as well as North America, Europe and Asia-Pacific, which matters for latency and data residency.
- Pay-as-you-go pricing plus discounts for committed usage, and free tiers or credits for new accounts.
For a typical web application with a database, any of the three will work well. The decision usually comes down to the points below.
AWS vs Azure vs Google Cloud: strengths compared
| Factor | AWS | Microsoft Azure | Google Cloud |
|---|---|---|---|
| Best known for | Breadth of services and maturity | Integration with Microsoft products | Data analytics, Kubernetes and networking |
| Natural fit | Startups, SaaS companies, mixed stacks | Windows, .NET, SQL Server and Microsoft 365 shops | Data-heavy and container-first teams |
| Identity | AWS IAM, IAM Identity Center | Microsoft Entra ID (formerly Azure AD) | Cloud IAM with Google accounts or Workspace |
| Signature services | EC2, S3, Lambda, RDS, DynamoDB | App Service, Azure SQL, AKS, Azure OpenAI | BigQuery, GKE, Cloud Run, Vertex AI |
| Talent availability | Very wide | Very wide, especially in enterprise IT | Narrower but growing |
Amazon Web Services
AWS launched its core services years before its rivals and still offers the widest catalogue. If a niche managed service exists, AWS probably has one. Documentation, community answers, third-party tools and Terraform examples are abundant, and finding engineers with AWS experience is relatively easy.
The flip side is complexity. The console and the IAM permission model can overwhelm newcomers, and there are often several overlapping ways to do the same thing. Billing has many line items, so set budgets and cost alerts on day one.
Microsoft Azure
Azure's biggest advantage is how well it fits organisations already built on Microsoft. Staff can sign in with the same Entra ID accounts they use for Microsoft 365, group policies and conditional access extend naturally, and Windows Server and SQL Server workloads are first-class citizens. Licensing benefits such as Azure Hybrid Benefit can let you reuse existing Windows Server and SQL Server licences with Software Assurance, which can significantly change the cost comparison for Windows-heavy estates.
Azure also has a strong hybrid story through Azure Arc and Azure Stack, useful if some systems must stay on premises. Some users find the portal and service naming less consistent than they would like, and service behaviour can vary by region, so check availability for your chosen region.
Google Cloud Platform
Google Cloud is often praised for clean design and developer experience. BigQuery, its serverless data warehouse, is a standout for analytics. Kubernetes originated at Google, and Google Kubernetes Engine is widely regarded as a mature managed Kubernetes offering. Cloud Run makes running containers without managing clusters very straightforward.
Google also applies some discounts automatically, such as sustained use discounts on certain VM types, which simplifies cost management. The main considerations are a smaller partner and talent pool in some markets and a narrower range of enterprise-oriented services compared with AWS and Azure.
Decision factors that matter more than features
1. Your existing software and identity
If your company runs on Microsoft 365 and Active Directory, Azure removes a lot of integration work. If your team lives in Google Workspace and your product is data-centric, Google Cloud may feel more natural. If you have no strong existing ties, AWS's breadth and ecosystem make it a safe default.
2. Your team's skills
The provider your engineers already know is often the cheapest one, because misconfiguration is expensive and learning curves are real. Factor in certification and hiring if you are building a team.
3. Specific services you depend on
List the managed services your architecture needs and check each exists in your target region with the features you require. A service available only in a distant region can undo the benefit of choosing a provider.
4. Support and partners
All three sell paid support plans with different response times. Free support is limited to billing and account questions, so budget for a support plan or a partner if production systems depend on it.
5. Exit cost
Data transfer out of any cloud is charged, and deep use of proprietary services increases lock-in. Using portable technologies such as containers, PostgreSQL or MySQL, and infrastructure as code keeps future options open.
A simple way to decide
- Write down your top five workloads and the managed services each needs.
- Use each provider's official pricing calculator to estimate those workloads in your preferred region.
- Run a small proof of concept on your top one or two choices for a few weeks.
- Score each on cost, fit, skills and support, then decide.
The official calculators are the only reliable source of current prices: AWS Pricing Calculator, Azure Pricing Calculator and Google Cloud Pricing Calculator. If you would like an independent second opinion, see our cloud solutions and software consulting pages.
Key takeaways
- All three providers are capable; a standard web app runs well on any of them.
- AWS leads on breadth and ecosystem, Azure on Microsoft integration, Google Cloud on data analytics and Kubernetes.
- Existing software, team skills and required services matter more than headline features.
- Compare with official calculators and a short proof of concept, not with published price lists.