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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
Amazon AWS is praised for cost-efficiency, scalability, quick deployment, and positive ROI, especially during critical periods like COVID-19.
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
6.8
Amazon AWS provides reliable customer service with skilled support staff, enhancing user satisfaction through responsive and knowledgeable assistance.
Sentiment score
6.3
Google Compute Engine support receives mixed reviews; some praise responsiveness while others note inadequate assistance and delayed responses.
Amazon AWS has good technical engineers available, making their customer service reliable.
 

Scalability Issues

Sentiment score
7.8
Amazon AWS is highly valued for its scalability and flexibility, effectively supporting diverse user needs and business applications.
Sentiment score
8.0
Google Compute Engine is scalable and versatile, suitable for varying workloads, with strong network and security features.
Amazon AWS provides strong scalability features, but the scaling process could be made more straightforward.
 

Stability Issues

Sentiment score
8.1
Amazon AWS is highly reliable and stable, with minimal downtime, though architecture design impacts performance, making it a preferred choice.
Sentiment score
8.3
Google Compute Engine is highly reliable with a 99.99% SLA, frequently surpassing performance expectations and stability compared to competitors.
 

Room For Improvement

Amazon AWS needs better cost transparency, user interface, integration, documentation, security, support, and training to enhance user experience.
Google Compute Engine users seek UI enhancements, expanded options, improved security, synchronization, and better support and marketing focus.
Amazon AWS could improve its user interface to make it more user-friendly, especially for people who are not highly technical.
 

Setup Cost

AWS pricing is scalable and competitive but complex, with tools available to manage potential unexpected costs for enterprises.
Google Compute Engine offers competitive, flexible pricing, often cheaper than Azure and AWS, with savings possible through resource optimization.
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 leads in cloud hosting with scalable services, pay-as-you-go model, robust infrastructure, and global reach.
Google Compute Engine offers customizable VMs, scalability, cost-effectiveness, security features, and diverse compute and storage options.
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
255
Ranking in other categories
PaaS Clouds (2nd)
Google Compute Engine
Ranking in Infrastructure as a Service Clouds (IaaS)
10th
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 March 2025, in the Infrastructure as a Service Clouds (IaaS) category, the mindshare of Amazon AWS is 14.7%, down from 22.9% compared to the previous year. The mindshare of Google Compute Engine is 0.6%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Infrastructure as a Service Clouds (IaaS)
 

Featured Reviews

Arun Srivastav - PeerSpot reviewer
Allows for automatic scaling of resources and provides built-in firewalls and security features, eliminating the need for external security solutions
One thing that's a bit different is that we're still accustomed to speaking to someone directly. AWS doesn't offer that kind of support. It's only through bots. You're speaking to chatbots, and that can sometimes be frustrating because there's no person on the other side. AI is not a substitute for a person. AWS marketplace is very strong, but somehow AWS doesn't promote it much. They have a huge customer base across the globe, and if products were launched in their marketplace, they could sell like hotcakes. They should improve their marketplace and promote the same product across the globe. They can take a cut, but they should promote it. That's something they don't do very much. So, AWS should promote its marketplace software. The company should promote it aggressively. Currently, they keep it very subtle. If you ask for it, they'll help you out. But they don't seem to advertise, "You're building a product on our platform? Why don't you sell it in our marketplace?" Improvement in AI: AWS is a little behind Microsoft Azure in terms of AI. AWS is still getting there, but the kind of examples and help files available in Azure for AI are much better. So AWS still needs to work on its AI functionality.
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
Educational Organization
28%
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
7%
Manufacturing Company
21%
Computer Software Company
16%
University
15%
Financial Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

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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: March 2025.
842,113 professionals have used our research since 2012.