AWS vs. Azure vs. Google Cloud Platform

Choosing between AWS, Azure, Google Cloud Platform, and Oracle can be challenging, whether planning a move to the public cloud or optimizing your cloud project.

They all offer flexible compute, storage, and networking along with everything engineers love about the cloud: self-service, instant provisioning, and autoscaling. 

However, these providers often differ in areas that may have a massive impact on your cloud bill. 

Selecting one vendor over another comes down to knowing what your teams, applications, and workloads need. It’s essential to fully understand your requirements before exploring the cloud landscape.

This cloud pricing comparison covers storage and compute pricing across the top three cloud providers AWS, Azure, and Google Cloud, as well as Oracle, to show you the nuanced differences between them. 

Cloud landscape today: What are the unique strengths of AWS, Azure, and Google Cloud Platform?

AWS

Companies choose to build their applications on AWS because of its breadth and depth of services. The rich array of tools, including databases, analytics, management, IoT, security, and enterprise applications, makes AWS the right solution for many teams. No wonder AWS has the most significant slice of the cloud market.

Azure

According to one survey, Azure adoption slightly surpasses AWS: 80% Azure vs. 78% AWS.Azure offers various services for enterprises, and Microsoft’s longstanding relationship with this segment makes it an easy choice for some customers. Azure, Office 365, and Microsoft Teams enable organizations to provide employees with enterprise software while leveraging cloud computing resources. 

Google Cloud Platform

Azure and AWS have strong machine-learning capabilities. However, the Google Cloud Platform stands out thanks to its almost limitless internal research and expertise – the magic that has been powering the search engine giant for years. 

What makes GCP different is its role in developing various open-source technologies. We’re talking especially about containers and Google’s central role in building Kubernetes for orchestration and Istio service mesh, which are practically industry-standard technologies today. 

Google’s innovation culture lends itself well to startups and companies prioritizing such approaches and technologies.

Billing in AWS vs. Azure vs. Google Cloud Platform

In addition to per-minute billing, AWS, Azure, and Google Cloud support per-second billing for various services. AWS first introduced per-second billing in 2017 for EC2 Linux-based instances and EBS volumes – but today, it applies to many other services. 

Per-second billing works with a minimum 60-second limit in AWS. Azure allows per-second charges on its cloud platform, but this billing model isn’t available for all instances – only some container-based ones. 

Google Cloud followed AWS in introducing per-second billing and now offers it for more than just Linux instances. This form of billing applies to all VM-based instances.

Cloud storage pricing comparison

How do these major cloud providers differ in terms of storage pricing? 

Here’s a comparison of prices in similar regions: AWS US East (Northern Virginia), Azure East US, and Northern Virginia (us-east4) in Google Cloud Platform.

These cloud service providers compete closely and set similar price ranges for storage services, with Azure being the most cost-effective alternative. However, check out other cost dimensions before choosing a storage service, such as data transfer or operations charges.

Also, pay attention to the provider’s approach to pricing changes. Google Cloud Platform recently introduced significant price increases across various core storage services, which may affect other services and cloud providers.

Compute pricing comparison

Compute often racks up the most in a cloud bill but presents the greatest opportunity for cost optimization. That’s why it’s an essential element in every cloud pricing comparison.

We prepared this case study to show the incredible impact optimizing compute costs can have on your bottom line.

Comparing cloud pricing: our example setup

To better understand the pricing differences, we will compare virtual machines within similar regions and with the same operating system.

The services analyzed are:

• AWS – Amazon Elastic Compute Cloud (EC2)
• Azure – Virtual Machines
• Google Cloud Platform – Compute Engine
• Oracle – Virtual Machines 

Our example setup:

• Region: AWS US East (Northern Virginia), Azure East US, and Northern Virginia (us-east4) in Google Cloud Platform.
• Operating System: Linux. 
• Number of vCPUs: 4.

Types of instances/VMs analyzed:

• General purpose
• Compute optimized

We picked instances with four vCPUs and similar memory (the only exception is the compute-optimized machine from the Google Cloud Platform). 

Here are the instances/VMs we selected for our cloud pricing comparison:

AWS vs. Azure vs. Google Cloud Platform: comparing On-Demand pricing 

Here’s the hourly On-Demand pricing for these cloud services across AWS, Azure, and Google Cloud Platform.

Cloud pricing based on On-Demand rates

General purpose

Compute optimized

Takeaways:

• While Azure offers the most expensive general purpose instance analyzed, it offers a good deal on the compute-optimized instance example.
• Google Cloud Platform offers the highest price for compute optimized instances, but this machine has double the RAM of AWS, Azure, and Oracle alternatives. 

x86 vs. Arm: impact on pricing

In the 2025 Kubernetes Cost Benchmark Report, we compared hourly Spot and On-Demand pricing for x86 and Arm CPUs across AWS, GCP, and Azure.

Our comparison showed some interesting trends:

• Arm CPUs consistently offer better value than x86 CPUs in both On-Demand and Spot pricing. This presents a significant cost-saving opportunity for those able to leverage Arm architecture.
• Azure stands out with the largest pricing gap between x86 and Arm CPUs—65% for On-Demand and 69% for Spot. For flexible, cost-sensitive workloads, Arm on Azure is particularly attractive.

If you want to trim cloud costs, Arm CPUs are worth considering, especially when using Spot Instances.

AWS vs. Azure vs. Google Cloud: comparing discounted pricing with a 1-year upfront commitment

All three providers offer price discounts if you commit to using them for at least one year. This pricing model is called Reserved Instances in AWS, Reserved Savings in Azure, and Committed Use Discounts in Google Cloud. 

The following tables compare the discounted pricing among AWS, Azure, and Google Cloud cloud services with a one-year commitment period with an all-upfront payment.   

Cloud pricing with a 1-year commitment

General purpose

Compute optimized

Takeaways: 

• AWS and Azure offer similar discount rates for general purpose instances with a one-year commitment.
• Google Cloud Platform offers the biggest discounts on both general purpose and compute–optimized instances—still, it’s not the cheapest option. Note that the compute-optimized GCP instance we picked has 16 GB RAM, not 8 GB like the other instances.

AWS vs. Azure vs. Google Cloud: comparing Spot Instances/Preemptible VMs

Another way to get discounts and reduce your cloud bill is to take advantage of capacity currently not used by anyone else. Cloud providers sell excess capacity at incredible discounts. AWS Spot Instances offer up to 90% off the On-Demand rates, and Preemptible VMs in Google can be even 80% cheaper than regular ones.

Here’s a quick overview of the potential savings you can get for these instances in the US East (Northern Virginia) region:

Cloud pricing with Spot Instances/Preemptible VMs

General purpose

*Note that we changed the machine type to a similar one with 4 vCPU and 8 GB RAM because Azure’s machines in Bs-series aren’t available as Spot Instances!

Compute optimized

Takeaways:

• Azure offers the greatest discounts for both general and compute-optimized instances.
• Oracle offers Preemptible VMs at a flat 50% discount.

To take advantage of Spot Instances, you must ensure your application can handle interruptions. How? Here’s a step-by-step guide: Spot Instances: How to reduce AWS, Azure, and GCP costs by 90%

Optimizing cloud costs is a real-time activity

Cloud providers change Spot Instance prices regularly. According to the 2025 Kubernetes Cost Benchmark Report, Azure and GCP offer more predictable pricing, with changes happening only a few times a month. 

On average, GCP sees a new price every three months (0.35 times/month), and Azure changes prices slightly less than once a month (0.76 times/month).

AWS, on the other hand, is much more dynamic. Spot prices fluctuate continuously, and AWS averages 197 distinct monthly price changes for GPU and non-GPU instances.

This means that teams relying on Spot Instances need to monitor prices and be flexible enough to change their setups.

That’s why you need automation to optimize cloud costs

Choosing the best compute instance for your workload is never a one-time exercise. Your requirements may change, and cloud providers may increase their prices. Having an automation solution make these decisions in real-time is a game-changer.

For example, the video creation platform PlayPlay used automation to move its Kubernetes workloads to more cost-efficient compute instances. The screenshot below illustrates a rebalancing operation in which Cast AI replaced 13 nodes without impacting service availability, saving PlayPlay $1,430 monthly. 

If you’re running your applications on Kubernetes, you can start with a free cluster savings report and see the instance type and resource amount Cast AI would automatically implement if it managed your cluster.

Author: Laurent Gill