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Amazon AWS vs Google Compute Engine comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 16, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.9
AWS offers cost savings, scalability, and agility with a pay-as-you-go model, attracting clients and reducing overhead.
Sentiment score
6.3
Compute Engine offers initial cost savings and performance boosts, but financial benefits and precise savings remain challenging to gauge.
 

Customer Service

Sentiment score
6.9
AWS is favored for reliable support and problem-solving despite concerns over response times and communication efficiency.
Sentiment score
6.3
Google Compute Engine support receives mixed reviews; some praise responsiveness while others note inadequate assistance and delayed responses.
Reaching out to them and talking is different from receiving a complete solution to your problem.
We have a direct line to Amazon AWS, with premium support and AWS members located within the company.
Amazon AWS has good technical engineers available, making their customer service reliable.
 

Scalability Issues

Sentiment score
7.9
Amazon AWS provides seamless vertical and horizontal scalability, supporting diverse customer needs from startups to large enterprises efficiently.
Sentiment score
8.0
Google Compute Engine is scalable and versatile, suitable for varying workloads, with strong network and security features.
The scalability of Amazon AWS is excellent.
Amazon AWS provides strong scalability features, but the scaling process could be made more straightforward.
Scale-out is usually good with Amazon AWS.
 

Stability Issues

Sentiment score
8.1
Amazon AWS is highly reliable with minimal issues, strong infrastructure, and stability often rated between eight and nine.
Sentiment score
8.3
Google Compute Engine is highly reliable with a 99.99% SLA, frequently surpassing performance expectations and stability compared to competitors.
If I am spinning up any managed service from the console, sometimes it fails to start up, and there will be no information about why it failed.
 

Room For Improvement

AWS users face challenges in cost, support, complexity, security, documentation, and features, with improvements needed in usability and integration.
Google Compute Engine users seek UI enhancements, expanded options, improved security, synchronization, and better support and marketing focus.
If I create a Glue job, that will create S3 buckets and other resources that have cost implications, but once I clean up a Glue job, it does not delete the other accessory resources.
Amazon AWS could improve its user interface to make it more user-friendly, especially for people who are not highly technical.
When using scripts for APIs to fetch data, they don't match the data exactly with the request.
 

Setup Cost

AWS offers scalable, flexible pricing suited for enterprises but requires careful management to avoid high costs from storage and data transfer.
Google Compute Engine offers competitive, flexible pricing, often cheaper than Azure and AWS, with savings possible through resource optimization.
After three to four years, if you are not managing it correctly, you will be paying more than an on-premise solution, which applies to all cloud providers, so you must regularly maintain and manage for efficiency.
Currently, Amazon AWS is known to be on the higher price range because popular and in-demand services often come at a premium.
 

Valuable Features

Amazon AWS offers scalable, secure, and flexible cloud services with automation, diverse tools, and excellent support for efficient resource management.
Google Compute Engine offers customizable VMs, scalability, cost-effectiveness, security features, and diverse compute and storage options.
I particularly appreciate the recommendation engines they have recently created on the services, such as Savings Plans recommendations and Reserved Instances recommendations, which are very helpful, along with the analyzers such as their IAM analyzer and Access Analyzer.
Overall, there is a lot of fine-grained flexibility that Amazon AWS provides compared to other platforms.
Amazon AWS offers flexibility and scalability.
In GCP, there's a custom configuration feature unlike AWS and Azure.
 

Categories and Ranking

Amazon AWS
Ranking in Infrastructure as a Service Clouds (IaaS)
2nd
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
257
Ranking in other categories
PaaS Clouds (2nd)
Google Compute Engine
Ranking in Infrastructure as a Service Clouds (IaaS)
13th
Average Rating
8.8
Reviews Sentiment
7.0
Number of Reviews
16
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Infrastructure as a Service Clouds (IaaS) category, the mindshare of Amazon AWS is 16.6%, down from 19.0% compared to the previous year. The mindshare of Google Compute Engine is 1.0%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Infrastructure as a Service Clouds (IaaS) Market Share Distribution
ProductMarket Share (%)
Amazon AWS16.6%
Google Compute Engine1.0%
Other82.4%
Infrastructure as a Service Clouds (IaaS)
 

Featured Reviews

Asif  Meem - PeerSpot reviewer
Managed cloud services have helped accelerate experiments with flexible configuration options
Sometimes the costs associated with spinning up a service, especially managed services, have implications. For example, if I create a Glue job, that will create S3 buckets and other resources that have cost implications, but once I clean up a Glue job, it does not delete the other accessory resources. Sometimes, I have to go hunting for what resources Amazon AWS might have provisioned and how it is costing behind the scenes. It can be complex depending on your level of expertise. It is not as easy to get started, especially when it comes to secure practices. Amazon AWS is more hands-on than other platforms.
Arundeep Veerabhadraiah - PeerSpot reviewer
A highly scalable and seamless platform which is easily automated
One of GCE's best features is the managed instance groups. We typically use managed instance groups for high availability. You can set certain parameters for managed instance groups where if the load of the computer or server increases beyond 80%, for example, the solution will automatically spawn another instance, and the load will be automatically divided between two systems. If the load is 80% of one of the VMs or GCEs, once the load is divided, it comes down to 40%, so the availability of your systems goes up. However, that all depends on the parameters or configurations we put on the instance group. You also have regular health checks on these managed instance groups, which are configurable. If these health checks determine something wrong with the VM, they will automatically kick off or spawn a new GCE instance. This way, the outage time is less. Previously, on-premises, unless somebody reported the issue to the helpdesk saying that a particular service was unavailable, then a support team would need to troubleshoot what went wrong, which takes a long time. At least 30 minutes to one hour. But by using these managed instance groups, we can reduce the outage time, and second, we can configure them with minimal resources, bringing down our cost. And if the load increases, the managed instance groups automatically respond to new things. Subsequently, our costs decrease. We have a wide range of VMs. There are general-purpose VMs that can be used for hosting general-purpose applications. If some of our applications are memory intensive, then we have a lot of VMs in the M1 series. We can use a range of memory-optimized VMs for these things. We have C-series VMs for compute-intensive applications. If we use some mathematical formulas and require a very high throughput from that, there are GPU-optimized VMs used for machine learning or 3D visualizations in rendering software. GPU-enabled VMs are pretty powerful and responsive. Again, the best part is that we can spin them up when we need them, and once we're done with our work, we can shut them down, allowing tremendous cost savings for any customer. Previously, if we wanted a very high-configuration VM, we had to own the entire hardware and have it on our on-prem data center. And once we'd done with a particular activity, the system would just be lying there on our premises. That is not the case now. We use and decommission it, so we're only billed for the time we're using the product. One of the best things is the preemptible VMs or Spot VMs. These are the cheapest VMs in Google Cloud, but it has a string attached to it where Google can shut down these VMs whenever Google teams split. You only get about 90 seconds notice before they shut down this particular VM. There are scenarios where customers can use these preemptible VMs, for example, when running a batch job. Batch jobs are run once or twice daily, depending on the customer's requirement. Once we are done running these batches, we can decommission the VM. Even if, in the middle of this batch job, Google shuts down these VMs, we can pick up the processing from wherever the VM left off. These are some of the beautiful things we have on Google Cloud concerning the Compute Engine.
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Comparison Review

it_user8586 - PeerSpot reviewer
Aug 14, 2013
Amazon vs Rackspace vs Microsoft vs Google: Cloud Hosting Services Comparison
Amazon Web Services, Rackspace OpenStack, Microsoft Windows Azure and Google are the major cloud hosting and storage service providers. Athough Amazon is top of them and is oldest in cloud market, Rackspace, Microsoft and Google are giving tough competition to each other and to Amazon also for…
 

Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
11%
Manufacturing Company
9%
University
7%
Manufacturing Company
26%
Computer Software Company
10%
Performing Arts
6%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business131
Midsize Enterprise48
Large Enterprise112
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise7
 

Questions from the Community

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How is SAP Cloud Platform different than Amazon AWS?
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Looking to compare Google Firebase, Amazon AWS, and Microsoft Azure
We like Google Firebase hosting and authentication and also the excellent cloud functionality. Our team found the flexibility of handling and dealing with the database through EDL to be very useful...
What do you like most about Google Compute Engine?
Everything is simple and useful. The initial setup is not challenging.
What is your experience regarding pricing and costs for Google Compute Engine?
Google resources are cheaper compared to AWS and Microsoft Azure. Among the three, Google is the cheapest option.
What needs improvement with Google Compute Engine?
Google has a lack of focus on their products. They have many products in various areas of the market, but they do not productize or appeal to the market effectively. They should concentrate on prod...
 

Also Known As

Amazon Web Services, AWS
No data available
 

Overview

 

Sample Customers

Pinterest, General Electric, Pfizer, Netflix, and Nasdaq.
Allthecooks, BetterCloud, Bluecore, Cosentry, Evite, Ezakus, HTC, Infectious Media, iStreamPlanet, Mendelics, SageMathCloud, Sedex, Treeptik, Wibigoo, Wix, zulily, Zync
Find out what your peers are saying about Amazon AWS vs. Google Compute Engine and other solutions. Updated: September 2025.
868,759 professionals have used our research since 2012.