AWS vs Google Cloud vs Azure: How the Big Three Compare

The short answer

For a typical website, API or mobile backend, any of the three will do: each offers virtual machines, managed databases, Kubernetes, object storage and serverless. The differences show up in the details:

• AWS has the widest service catalog and the largest community, so specialists and ready-made solutions are easier to find.
• Google Cloud is strong in data analytics (BigQuery), managed Kubernetes (GKE) and AI services.
• Azure is the natural fit if your company already lives in the Microsoft ecosystem: Microsoft 365, Entra ID, .NET, Windows Server.

The deciding factor is rarely "which cloud is best" and more often "what does your team already know".

Services: what each one calls things

Core services are mature everywhere. Differences appear in niche areas: stream processing, specialized databases, ML tooling, IoT.

How pricing works

The model is similar across all three: pay as you go for compute time, storage, requests and outbound traffic. Discounts come from commitments:

• AWS: Savings Plans and Reserved Instances for 1- or 3-year commitments, Spot Instances for interruptible jobs.
• Google Cloud: Committed Use Discounts, automatic sustained use discounts on some machine types, Spot VMs.
• Azure: Reservations, Savings Plan, Spot VMs and Azure Hybrid Benefit if you already own Windows Server or SQL Server licenses.

What teams usually underestimate:

• Egress traffic is billed by all three and can become a noticeable line item if you serve a lot of content.
• Managed services cost more than raw VMs but save administration time.
• Prices vary by region, so the same machine costs differently in different locations.

Use each provider's official pricing calculator and compare a concrete configuration, not the price of "one server".

Regions near Central Asia

At the time of writing, none of the three has a region in Uzbekistan or neighboring countries. The closest options usually lie in three directions:

• Europe: Frankfurt, Warsaw, Stockholm and others.
• Middle East: UAE, Bahrain, Qatar, Saudi Arabia (availability depends on the provider).
• India: Mumbai, Delhi, Hyderabad, Pune (again, provider-specific).

Measure latency from Tashkent to specific regions yourself, since geography and network routes do not always match. Also check data localization rules: if the law requires personal data to stay in the country, a foreign region will not work for that part of your data.

Free tiers

All three offer starter deals for new accounts: trial credits plus always-free limits on some services. Terms change regularly, so:

• read the current free tier page before you start;
• set up budgets and spending alerts right away, because a forgotten resource can burn through credits quickly;
• never plan production around the free tier.

How to choose: a quick checklist

1. What does your team know? Prior experience with one cloud saves months.
2. Which managed services do you actually need, and are they available in your target region?
3. Where are your users, and are there data residency requirements?
4. Which ecosystem do you already use: Microsoft 365, Google Workspace, your own servers?
5. How will you pay: are suitable payment methods and invoicing available for your company?

A common mistake is choosing based on the price difference of a single VM. On a real bill, traffic, managed databases and engineering time matter far more.