AWS Vs. Azure Vs. Google Cloud: Which One Should You Use?

Combined, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) control 67% of the global cloud computing services market. That’s a big deal, but not for obvious reasons.

Here’s the deal.

Azure, AWS, and GCP all have vast experience managing cloud infrastructure. This can mean better services, engineering training, and superior technical support for you.

In addition, they have the resources to drive innovation and back up your data worldwide. And, because of their well-known status, they hold themselves to a high standard of accountability.

All of these factors combined mean you are more likely to choose one of these cloud service providers (CSPs) than others.

Yet, unless you’re considering a multi-cloud strategy, you’ll only need one cloud provider. And even if you plan to work with all three providers, you still need to know which vendor is right for particular services you require.

In this in-depth guide, we’ll cover the crucial differences between AWS, Azure, and GCP, including strengths, pricing, and more.

Table Of Contents

What Is Amazon Web Services (AWS)?

With 34% of the global cloud services market, AWS is the world’s largest cloud service provider. It offers more than 200 cloud services, from compute to edge to serverless computing.

A few of them are Amazon EC2 for compute; Amazon S3 for elastic object storage; Amazon EBS for networking; and Amazon Lambda for serverless; as well as Amazon RDS for relational database).

If you’re looking for a public cloud provider that delivers cloud infrastructure (Infrastructure-as-a-Service or IaaS), pay-as-you-go pricing, and autoscaling resources, AWS is a great choice.

With IaaS, AWS provides servers, networking, compute, and storage resources for you to deploy your workloads in the cloud; no need to buy, install, or maintain your own infrastructure.

What Is Azure Cloud?

Azure is Microsoft’s cloud services arm and a part of its Microsoft Intelligent Cloud ecosystem. Azure Cloud, like AWS, offers a variety of options for your engineers, including IaaS and Platform-as-a-Service (PaaS), and a little bit of Software-as-a-Service (SaaS) cloud models.

In PaaS, the vendor provides the platform on which you can build, host, and deploy your own consumer-facing applications.

And, by far the most popular model among small and medium businesses, SaaS allows you to subscribe to ready-made applications, customize them slightly, and use them as you see fit, but for particular purposes.

There are several reasons why Azure is most popular with enterprises. Here are two that stand out:

So, how does the Google Cloud Platform compare?

What Is Google Cloud Platform (GCP)?

GCP is best suited for companies that have cloud-native applications, including containers, Kubernetes, and Google Workspace. After all, Google pioneered Kubernetes (container orchestration platform), Istio (service mesh), and several other industry-standard tools.

Moreover, the technology that supports Google’s Search feeds the platform’s machine learning, artificial intelligence, and data analytics tools.

GCP is also popular with startups that want to leverage open-source, but tested platforms to accelerate their growth. Also, agile scaleups typically leverage its rapid cloud technology innovations to increase revenue and market share.

Now, putting specialties aside. In what ways do AWS, Azure, and GCP differ?

AWS Vs. Azure Vs. GCP: A Quick Comparison

	Amazon Web Services	Microsoft Azure	Google Cloud Platform
Launched	2006	2008	2011
Availability points	450+	160+	112+
Strength	Infrastructure-as-a-Service (IaaS)	Platform-as-a-Service (PaaS)	Database-as-a-Service (DaaS)
Services	237+	172+	100+
Strongest areas of cloud deployments	Public cloud, private cloud on AWS	Public, Hybrid cloud, On-premises	Public cloud, Multi-cloud
Pricing	Pay-as-you-go, by product/service	Pay-as-you-go, by product/service	Pay-as-you-go, by product/service

AWS Vs. Azure Vs. GCP: 9 Key Differences That Make The Difference

The three share all the essential attributes of a public cloud platform, such as self-service, instant provisioning, autoscaling, compliance, and identity management features for security. Here are some ares where Azure, AWS, and GCP have notable differences.

1. Availability Zones

Amazon Web Services cloud infrastructure spans 99 Availability Zones (with an additional 15 in the works) across 31 regions (with another 5 due to launch soon).

AWS Availability Zones

The provider offers 450+ points of presence as well as Edge computing points on every continent except Antarctica. A large network offers seamless scalability, low latency, multi-region data backup, and several more benefits.

Microsoft Azure’s global network of over 160 data centers ensures high availability as well.

Azure Availability Zones in the US

Each Azure Region offers three separate Availability Zones, each with independent power, cooling, and networking infrastructure in case one or two zones experience issues.

GCP also provides cloud services through the Regions and Zones concept (37 Regions, 112 Zones, and 176 Edge locations).

GCP Regions worldwide

Bringing these services closer to the end user translates to low latency and boosts overall workload performance. GCP Regions also offer two or three independent Zones to ensure resilience in case of failure or issues in one or two zones.

Depending on the region or AZ, each CSP offers different levels of service. It is possible that a particular service is available in that location but that its capabilities are limited compared to those in other locations. These are some of the details you’ll want to carefully confirm before buying in.

2. Services

AWS offers over 237 fully featured cloud products and services in 2023, the most by any CSP. The vendor organizes its services and products across categories, including compute, storage, networking, serverless, databases, analytics, security/compliance/identity management, and databases.

AWS cloud services and products categories

Similarly, Azure Cloud offers a wide range of cloud services, with multiple products under each cloud service category.

Azure cloud services and products

While the Google Cloud Platform seems to offer fewer products, at just over 100, you are likely to find the solution you need. Check this out:

Google Cloud Platform services and products

Again, before choosing a provider, be sure to review their service specifications thoroughly to ensure that they will meet your workload requirements.

3. Compute, storage, and networking

The vendors group their instances or virtual machines into different categories based on their suitability to specific workloads, such as:

For workloads that require balanced compute, memory, and networking resources, all three also offer general-purpose instances and bare metals.

As far as size goes, GCP’s M2 series virtual machin, which features 12 TB RAM and 416 virtual processors, is the largest of the three cloud service providers. In comparison, AWS and Azure offer instances with a maximum of 128 virtual CPUs and 3.84 terabytes of RAM and 128 virtual CPUs and 3.89 terabytes of memory, respectively.

Now, we get it. Finding the right instance type or virtual machine for a specific use case can be tough. A trial-and-error approach might not be feasible for you, and you may not have the funding and luxury to experiment.

That’s why we recommend using CloudZero Advisor, our free tool that helps you pick just the right machines by instance or VM type, size, and service, as well as by your budget, workload, and other factors.

Something else. You can run Linux or Windows machines on Azure, GCP, and AWS. Azure allows you to use your existing Microsoft licenses, whereas GCP and AWS require additional Windows licensing costs.

AWS, Azure, and GCP share a lot of similarities in terms of storage, such as fast SSDs, cheaper hard drives, and multiple archiving options. All three vendors also offer object, file, persistent block, and other types of cloud storage.

Some differences here include:

On to the next.

4. Open-source support

AWS has a long history of working with open-source communities. From Apache Kafka to Linux to MySQL to OpenTelemetry, AWS has supported notable projects.

Plus, to enable developers to switch from proprietary to open source software, it also open-sourced projects like .NET Porting Assistant and Babelfish for PostgreSQL.

But Google goes even bigger here. Among Google’s Open Source projects are Kubernetes (container orchestration), Istio (service mesh), TensorFlow (machine learning), and Go (programming language), most of which it donated to the Cloud Native Computing Foundation (CNCF). If you intend to integrate or leverage such platforms or tools, GCP may be the best choice.

The Azure cloud platform is increasingly supporting open source projects, but they are still handled by third parties such as RedHat, Terraform, and Databricks.

5. Containers

Each vendor offers a managed Kubernetes solution to simplify K8s deployments; Amazon Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), Google Kubernetes Engine (GKE).

However, AWS also offers the Amazon Elastic Container Service (ECS) for Docker containers. Amazon ECS is also a managed container service that leverages AWS security features and native tooling (such as Amazon ECR for storing, encrypting, and managing container images for speedy deployments) to further ease K8s deployments.

You can also provision, run, and self-manage Kubernetes on AWS using Amazon Elastic Compute Cloud (EC2) instances. Self-managing Kubernetes on Azure or GCP isn’t as straightforward.

In addition, it also costs an extra $0.10 per hour per cluster to run containerized apps with EKS vs ECS.

6. Artificial intelligence, machine learning, and data analytics

The three offer unique, yet very similar, big data, predictive analytics, and data lakes for AI and machine learning. GCP, however, currently offers the most advanced Deep Learning models and powerful hardware accelerators (Cloud TPUs).

Meanwhile, AWS and Azure each feature ML studios dedicated to developing machine learning models. Yet, Azure’s studio does not require a deep knowledge of data engineering, Python coding, or open-source libraries like Amazon SageMaker does.

7. Support and pricing

Cloud services tend to be similar in terms of functionality, but prices are often a key differentiating factor. Still, Azure, GCP, and AWS pricing is similar in that they all use a pay-as-you-go model, with varying prices depending on whether you use the resources on-demand or on a reserved basis (committed use).

Here are some notable highlights for each CSP:

About GCP pricing:

About AWS pricing:

About Azure pricing:

Check out this AWS vs Azure pricing comparison for an in-depth guide on what costs to expect.

8. Uptime and latency

Azure, AWS, and GCP all claim 99.99% (four nines of uptime). However, their Service Level Agreements (SLAs) often guarantee 99.5% uptime for some services and 99.99% for others.

For exact guidelines, the AWS SLAs page details how compensation for service unavailability works (earning service credits for lower than promised uptime). Azure SLAs page also talks about this variation in more detail as does GCP SLA documentation.

Amazon Web Services: Pros And Cons

Below are some of the advantages and disadvantages of the Amazon Web Services platform.

AWS Pros

AWS Cons

When should you use AWS?

AWS services are suitable for organizations of all sizes, in any industry, on any budget, and located anywhere in the world. With its extensive service options, IaaS and PaaS infrastructure, and pay-as-you-go (usage-based) pricing, AWS is the gold-standard of cloud computing. The CSP is also ideal for advanced machine learning and data backup.

Microsoft Azure: Pros And Cons

The Microsoft Azure cloud has some benefits and drawbacks, too.

Azure Pros:

Azure Cons

When should you use Azure?

The best choice for large enterprises, especially those who already use Microsoft products and licenses, such as Microsoft 365 and Windows SQL Server.

Microsoft Azure is also ideal for hybrid cloud deployments in which enterprises want to use local or private clouds alongside public cloud services.

Google Cloud Platform: Pros And Cons

Below are some of the disadvantages and advantages of the Google Cloud Platform to watch out for.

GCP Pros:

GCP Cons

When should you use GCP?

GCP is ideal for SMBs with cloud-native operations and looking to leverage cloud-native processes, AI, ML, and data analytics for growth. It is also ideal for companies looking to use GCP alongside two or more public clouds.

How To View, Control, And Reduce AWS, Azure, And GCP Cloud Costs

With so many products, services, and processes available, these vendors offer a great deal of flexibility.

The downside is the complexity poses a huge cost blindspot, making it nearly impossible to understand, track, and optimize cloud costs with ease.

That explains why companies waste about 30% of their cloud budgets.

The fact that AWS, Azure, and GCP offer basic cloud cost management tools doesn’t help either. With their basic tools, it’s hard to tell what’s driving your cloud costs, because they only provide totals and averages.

Enter CloudZero’s cloud cost intelligence approach

CloudZero uses a code-driven approach to consolidate, analyze, and share detailed cost insights that can be applied immediately. No overwhelm. No endless cost allocation tags required.

But that’s not all. CloudZero also empowers you to:

These capabilities and more helped us find over $1.7 million in annualized savings. Drift saved $2.4 million in annual costs using CloudZero. This is something you can also do. to see how CloudZero can help.