Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing services. With over 165 services offered, AWS services can provide users with a comprehensive suite of infrastructure and computing building blocks and tools.
$100
per month
Google Compute Engine
Score 8.3 out of 10
N/A
Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.
$0
per month GB
Pricing
Amazon Web Services
Google Compute Engine
Editions & Modules
Free Tier
$0
per month
Basic Environment
$100 - $200
per month
Intermediate Environment
$250 - $600
per month
Advanced Environment
$600-$2500
per month
Preemptible Price - Predefined Memory
0.000892 / GB
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Hour
On-demand price - Predefined Memory
$0.004237 / GB
Hour
Preemptible Price - Predefined vCPUs
0.006655 / vCPU
Hour
Three-year commitment price - Predefined vCPUS
$0.014225 / CPU
Hour
One-year commitment price - Predefined vCPUS
$0.019915 / vCPU
Hour
On-demand price - Predefined vCPUS
$0.031611 / vCPU
Hour
Offerings
Pricing Offerings
Amazon Web Services
Google Compute Engine
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
AWS allows a “save when you commit” option that offers lower prices when you sign up for a 1- or 3- year term that includes an AWS service or category of services.
Prices vary according to region (i.e US central, east, & west time zones). Google Compute Engine also offers a discounted rate for a 1 & 3 year commitment.
OCI and Google Compute Engine are a bit cheaper than AWS but AWS has better chargeback and more granular monitoring of various KPIs. But at the same time, AWS has a learning curve while GCE especially is much easier to use. Microsoft Azur has a much better partner and developer …
The decision was made to go with AWS because of name recognition and familiarity by contractors we hired. I checked out Google Compute Engine a few years ago, and it did have similar option set, however Google in general was behind Amazon's offerings.
Google Cloud lacks the features and compatibility of the other cloud providers. It makes up for that with highly specialized and perfected services like their Big Data and Query features.
After all the discounts, GCE is a bit cheaper with much less incidental expenses to deploy and maintain compared to Amazon, Microsoft Azur and Oracle (OCI). It is also easy to manage as the interface is simpler compared to AWS or Azur.
AWS's UI could use a lot of work, and their API documentation was much worse compared to Google's, which was already tough to read and figure out. Google's free trial of their services through a platform credit (which AWS doesn't offer), also helped us test their compute …
I've used Rackspace, AWS, and Digital Ocean to host virtual environments. In my opinion, GCE has a robust feature set on par with any other mainstream virtual hosting company. I would say AWS and Digital Ocean are comparable, and Rackspace would be slightly less robust than …
AWS has a ton of options in terms of tools that you can use. It's pricing model is hit or miss (some offerings are simply unaffordable). Some of the API design is questionable at best and frustrating at worst. Microsoft Azure is a newcomer in the market with focus on enterprise …
For this particular use-case Google Compute Engine was the better platform as this was a focused development and did not require bespoke infrastructure to support it. The service offered allowed the opportunity to embed core Google apps and services to deliver a quality service …
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Google Compute Engine is so easy to implement and run. It doesn't require much knowledge to build an app since they provide multiple options to choose from with their prebuilt sample list. We can easily make customization on any website app we built for our client according to their needs and make changes if required.
Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs
If there is one thing I think AWS needs improvement on, it is the administration dashboard. It can be a nightmare to use especially when trying to access billing. This could be made better, honestly, as there should be a simplified way to access simple admin features.
While AWS was fairly easy to integrate into our solutions, it is not as easy to use without some IT knowledge. The dashboards are complicated and designed for someone who is computer savvy. If you are just want to keep track of billing, for example, you may need to take a course or spend a few hours with someone being walked through the admin console.
AWS does tend to be slow at times. If you do not have a fast internet connection, it can take time to access services that are hosted on AWS. This is not always the case but we have had clients complain about this if they are trying to access a service from multiple points (IP addresses). The only real fix we found was to make our files cache to another server and only keep current data accessible to clients.
We are almost entirely satisfied with the service. In order to move off it, we'd have to build for ourselves many of the services that AWS provides and the cost would be prohibitive. Although there are cost savings and security benefits to returning to the colo facility, we could never afford to do it, and we'd hate to give up the innovation and constant cycle of new features that AWS gives us.
Our cloud platform architecture was designed in order to collect, analyze, and optimize modern networks, from AWS-powered computing, networking, storage, and more. So, we needed a reliable, scalable, and secure global computing infrastructure. Auto Scaling and Elastic Load Balancing were key features in our evaluation and later on for scalability and high performance. We being a cybersecurity company, we needed to ensure that our cloud provider utilizes an end-to-end approach to secure and harden the infrastructure, including physical, operational, and software measures - which AWS had all in place.
Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.
There were some very few cases where we had an outage but mostly it did not last more than 10 minutes. And if there were any maintenance, we were notified beforehand. So did not have any major problem with Google Compute Engine's availability.
AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.
GCE is a performant infrastructure. The GCE usage reports are readily available and the reports load time is insignificant. GCE exposes various REST API which allows the third part system to integrate with GCE. Many observability software like newRelic integrates with the GCE to offer monitoring of GCE
The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to immediately search for their compatible software's and also to guide them in a good direction. Moreover, this product is a good suggestion for every type of company because of its affordability and ease of use.
The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
Google support was great and their presence on site was very helpful in dealing with various issues.
Amazon Web Services is well suited when we have a huge amount of data to store, process, manipulate and get meaningful information out of. It is also suitable when we need very fast data retrieval from the database. They provide a superior product at a fair price which allows us to further our goals and push the limits of what we are capable of as a team / company.
Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.
