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.
$0.01
Hour
Microsoft Azure
Score 8.5 out of 10
N/A
Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
Pricing
Google Compute Engine
Microsoft Azure
Editions & Modules
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
Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
Offerings
Pricing Offerings
Google Compute Engine
Microsoft Azure
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
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.
The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
More Pricing Information
Community Pulse
Google Compute Engine
Microsoft Azure
Considered Both Products
Google Compute Engine
Verified User
Anonymous
Chose Google Compute Engine
Rather than saying GCE is better. I would say that depends on the business and technical requirements it might fit better than others. There is no silver bullet.
I actually prefer Azure's UI over Google Compute Engine's , but Google Compute Engine's pricings are way more competitive, which makes it the go-to choice for infrastracture low budget companies such as ours, since our core business is not IT or software development related
Cloud providers offering virtual machines are quite common. I think, Google, however, is arguably one of the top players in the market, with some of the largest (if not the largest) and most advanced server farms in the world. If you're looking for reliability and cost …
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
We have tried using DigitalOcean droplets for some of our minor and non critical VMs. In our experience, Google Compute Engine fares well in comparison the DigitalOcean droplets as they provide better availability, better support and in general, a better experience.
As far as user-friendliness is concerned, I personally rank Google Cloud above both AWS and Azure. Their user interface makes it easy to manage, which is important.
I find Google Compute Engine to be much easier to use than Amazon's EC2 service. The console makes much more sense, permission management is much cleaner, and I'd say the other categories feel on par with EC2: performance, how fine-grained the settings are, connecting to …
The obvious and natural alternatives to GCE are AWS EC2 and Azure VMs. I would say all three are more similar than not. Picking one will most likely depend on what platform you're on already, where your running services are, and which one is more familiar to your team.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an …
The Google Cloud computing engine is fair at the top because it bills customers, automatic discounting for extended use, and how fast it can be turned on. We enjoy things around setting it up very easily via APIs and CLI commands, and with the always-on recommendations from …
I have utilised Google Compute Engine in addition to Amazon EC2. Both exhibit excellent performance in terms of consumption, speed, and efficiency.My decision to adopt Google Compute Engine was solely based on how user-friendly it is. more basic UI/UX than EC2.Google's customer …
Google Compute Engine provides on-demand computing resources that are easy to scale up or down according to my organization needs. This allows our business to quickly adapt to changes in demand without having to invest in additional hardware. It also offers a very competitive …
While Amazon EC2 is the best tool for developers to build an app and make it live, It has some downsides too. EC2 requires so much development while Google Compute Engine makes it easy to build an app within a days. EC2 pricing also relatively high compare to Google Compute …
GCE is available in 3 different regions whereas Ec2 is available in 11 different regions. The compute resources offered by the GCE has lower maximum capacity compared to AWS Ec2. The pricing model of GCE offers first 10 mins free and then charging in increments of 10 mins. Both …
I prefer the Compute Engine Over these as it provides us with Better Scalability, Performance, and Reliability Security-related Issues don't arise with the Compute Engine, but yes, in terms of accessing or running, it can be improved a bit as compared to EC2 offered by AWS.
the main reason of choosing GCE is availability and user friendly UI with a very good documentation and API explanations. Great visibility over the infra and security.
The features specific to Google Compute Engine vs Amazon EC2 along with cost and availability are comparable, there may be other services within the vendor which may mean that one is more suitable for specific applications than the other one. We have used both for different …
Obviously this is just based on the virtualisation part of the product, but VM's in Microsoft Azure are well managable and no need to invest in hardware, which gives it an edge in a time where the need for VM's is getting less and less.
I feel that Microsoft Azure typically outperforms Google Cloud Platform in hybrid cloud capabilities, integration aspects, and, primarily, security compliance features. Azure offered superior integration with Microsoft's enterprise software ecosystem, and it's second to none in …
Mostly due to the ecosystem. I don't think there is anything in AWS that we would be missing out when using Microsoft Azure. We use Microsoft products on on-premise servers and also M365 / Office services that are well supported in Microsoft Azure. The pricing between AWS and …
AWS is good for linux virtual machines and mac virtual machines, Microsoft Azure doesn't do mac VMs. However, in my opinion Microsoft Azure is better in every other aspect, easier to use and just as cost effective.
AWS takes the cake here just due to how simple it is to configure IAM roles, users, and policies. Microsoft Azure is nearly neck-and-neck and could probably overtake them in the near future. Splunk for logging isn't that great and Microsoft Azure does a solid job but they could …
Microsoft Azure is a comprehensive platform that offers almost all functionalities and can provide even more. Due to ongoing extensive developments, additional functionalities are continuously being added and improved. Many new functionalities are also being added that are …
AWS is the most stable cloud options but Azure has done well in last few years and provides good options specifically for Microsoft customers and who are more familiar with Microsoft technologies like WINDOWS, MS SQL SERVER, GITHUB, VISUAL STUDIO etc. Google cloud is more …
Azure is an ideal platform for disaster recovery and backup. It is very flexible because of its site regeneration capabilities and other features. All of our data can be backup, regardless of the language or operating system. Azure’s inherent flexibility comes from its status …
Remote accessibility for the mass people from the different places where both free and premium service is available that's why people choose Microsoft Azure. The main reason of switching from that to Microsoft Azure is the cost of operation and operating flexibility. The …
AWS and Azure are distinct classes, regardless of how we view them or which sub-areas. Their capabilities are the most comprehensive and sophisticated. Azure will benefit existing Microsoft customers, but AWS has a slight market share advantage. Microsoft Azure offers many …
Because Microsoft Azure has more integrations and possibilities. Also most of the biggest companies are using it, so it gives the security and the back up to trust and work with confidence.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" …
We actually utilized multiple cloud stacks, depending upon the customer environment and need. Those that heavily used MS products (Office on-prem or 365), Teams, etc, found it a better fit, with easier integration, for their needs.
I would say that Azure stacks up pretty good and sometimes better in comparison to what Google Cloud Platform has to offer. I don't like GCP for its absurd licensing fees and it's expensive for just Using EC2 Instances. However, DigitalOcean and AWS can offer far better …
The most common alternatives are Amazon Web Services and Google Cloud Platform. AWS is known for its non-existent customer support and abysmal documentation - Azure is clearly better on both fronts. Google Cloud Platform is a solid product, but in my experience Azure Functions …
Integration with other Microsoft products makes Azure stand out quite a bit. However, if you need to use open source software and to integrate with Linux systems then AWS or Google Cloud might be better alternatives. Google did not even come close to Azure in terms of …
We have not tried any alternatives to Microsoft Azure. To cater to our needs, Microsoft Azure was our primary option and it goes well so far. Apart from the application that hosted in service fabric we use azure for other needs like virtual machines, databases. As all our …
It is excellent if you have any workloads that need raw computing or plan to have any state-full services running in your environment like DBs (for which you don't want to use Managed services), cache, etc. It also gives you complete control over which versions of software, OS, etc., you need, and thus, you can build anything and deploy it on GCE.
Actually, migrating to Microsoft Azure is a good solution for almost any situation, especially when all components of your network are ready to become cloud-based. The only drawback I personally encounter frequently is that older software packages cannot always be easily picked up and moved to Microsoft Azure in an optimal manner.
A simple web-based interface that is a breeze to train new engineers to use. Our experienced engineers never have trouble finding or doing anything on GCE.
Sustained use and Committed use discounts mean we get top-tier VMs for an incredibly competitive price.
Wonderful identity and access management that gives us peace-of-mind when granting access to machines to contractors and other 3rd parties.
Fast VMs, lastest in hardware, and enough RAM to power even the hungriest of our services.
Azure simply provides end to end life cycle. Starting from the development to automated deployment, you will find [a] bunch of options. Custom hook-points allow [integration] on-premise resources as well.
Excellent documentation around all the services make it really easy for any novice. Overall support by [the] community and Azure Technical team is exceptional.
BOT Services, Computer Vision services, ML frameworks provide excellent results as compare to similar services provided by other giants in the same space.
Azure data services provide excellent support to ingest data from different sources, ETL, and consumption of data for BI purpose.
The L7 load balancer can be difficult to get set up. It's limited in its functionality, especially with the container engine.
It's hard to find certain objects on the web console. Often times the things I need to get to are buried in advanced menus.
Google's decision to only support MySQL on their relational DB service means that I have to manage Postgres instances in Compute on my own, managing everything from storage to backups.
In our experience, Azure Kubernetes Survice was difficult to set up, which is why we used Kubernetes on top of VMs.
Azure REST API is a bit difficult to use, which made it difficult for us to automate our interactions with Azure.
Azure's Web UI does a good job of showing metrics on individual VMs, but it would be great if there was a way to show certain metrics from multiple VMs on one dashboard. For example, hard drive usage on our database VMs.
Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.
We have been very satisfied with Windows Azure and now a lot of our business depends on it as more teams are now deploying their applications into Azure. Our next step is to have our Infrastructure team move their resources to Azure. It will take awhile for that to happen but we are positive that it will.
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.
Microsoft Azure's overall usability has been better than expected. Often times vendors promise the world, only to leave you with a run-down town. Not the case with our experience. From an implementation perspective, all went perfect, and from the user-facing experience we have had no technical issues, just some learning curve issues that are more about "why" than "how"
Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes
Google Compute Engine usually delivers good and predictable performance for our self-hosted stack of applications. However, when running n8n heavy workflows, even with a tunned instance configuration in docker, performance usually peaks usually due to memory usage. We often need to upgrade memory when we have heavier data processing and workflows. Other than that, in a normal usage, we don't really have any problems
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.
Support is easy with all the knowledge base articles available for free on the web. Plus, if you have a preferred status you can leverage their concierge support to get rapid response. Sometimes they’ll bounce you around a lot to get you to the right person, but they are quite responsive (especially when you are paying for the service). Many of the older Microsoft skills are also transferable from old-school on-prem to Azure-based virtual interfaces.
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an in-browser option; instead, it is Azure Bastion, but for that, you have to enable a dedicated subnet, which is a bit unnecessary.
I feel that Microsoft Azure typically outperforms Google Cloud Platform in hybrid cloud capabilities, integration aspects, and, primarily, security compliance features. Azure offered superior integration with Microsoft's enterprise software ecosystem, and it's second to none in my opinion. This made it the natural choice for most, especially if heavily invested in Windows, Office 365, or Active Directory deployments. We chose Azure over GCP because we simply needed Windows workload support as a strong driver, more access to global regions, and let's not forget that most tech teams in an organization are Microsoft Certified, which makes skillset transfer from on-prem to cloud a minimal learning curve over shifting to a different provider.
Scalability means flexibility and less upfront costs
Can become expensive when hard set compute requirements are clear, but things like Spot VMs can help here too, or just having your own infrastructure and scaling up with Google. This is for more advanced cases though
Ramp up time is long, but after that it is quick to do many things and ROI is awesome
Times and growth went into it. By balancing on-premises maintenance with continuous cloud improvements, we’ve budgeted and planned endlessly increased capacity.
In today’s world of cyber-crime, clients can put even more faith in what they’ve heard. We built an innovative single-sign-on hub for all users. Also, other business platforms use Azure application gateways, reducing worker switching time and increasing productivity.
Its step can automate to improve the investment. In addition, we can integrate our organization’s credentials into an authorization for other systems.