Google Compute Engine vs Microsoft Azure: What are the differences?
Google Compute Engine: Run large-scale workloads on virtual machines hosted on Google's infrastructure. Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance; Microsoft Azure: Integrated cloud services and infrastructure to support computing, database, analytics, mobile, and web scenarios. Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
Google Compute Engine and Microsoft Azure can be categorized as "Cloud Hosting" tools.
Some of the features offered by Google Compute Engine are:
- High-performance virtual machines- Compute Engine’s Linux VMs are consistently performant, scalable, highly secure and reliable. Supported distros include Debian and CentOS. You can choose from micro-VMs to large instances.
- Powered by Google’s global network- Create large compute clusters that benefit from strong and consistent cross-machine bandwidth. Connect to machines in other data centers and to other Google services using Google’s private global fiber network.
- (Really) Pay for what you use- Google bills in minute-level increments (with a 10-minute minimum charge), so you don’t pay for unused computing time.
On the other hand, Microsoft Azure provides the following key features:
- Use your OS, language, database, tool
- Global datacenter footprint
- Enterprise Grade with up to a 99.95% monthly SLA
"Backed by google", "Easy to scale" and "High-performance virtual machines" are the key factors why developers consider Google Compute Engine; whereas "Scales well and quite easy", "Can use .Net or open source tools" and "Startup friendly" are the primary reasons why Microsoft Azure is favored.
9GAG, Snapchat, and CircleCI are some of the popular companies that use Google Compute Engine, whereas Microsoft Azure is used by Microsoft, Starbucks, and Accenture. Google Compute Engine has a broader approval, being mentioned in 592 company stacks & 427 developers stacks; compared to Microsoft Azure, which is listed in 497 company stacks and 470 developer stacks.
What is Google Compute Engine?
What is Microsoft Azure?
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Windows Azure is more difficult to configure than some other cloud based technologies, however, it makes up for it with the incredible integrations and ease of development on mobile platforms (Android, iOS and of course Windows Phone).
The Azure Web Sites is a PaaS that is very easy to setup and is pretty powerful.
If you want VMs you can have them and even program when they come online.
There are tons of ways to use this service and there are a lot of free things you can get in order to try it out. The only downside is that you have to learn a new, although very powerful, platform.
I use Google Compute Engine instances as flexible, reproducible infrastructure that scale with my data science tasks.
Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
- I use Google Compute Engine instances as flexible, reproducible infrastructure that scales with my data science tasks.
- Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
- Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
We use Microsoft Azure because many of our clients are already Azure for their private cloud. Additionally, Azure supports App Service Environments (ASE), which isolates the application resources and gives us a static IP for securely accessing external resources
Additionally, MSSQL supports columnstore tables which is critical for running fast analytics over large datasets
My favourite cloud with all the great tools - web apps, mobile apps, storages, easy tables, blobs, app insights, cosmos DB... I think it is really usable and ergonomic. Plus point for mobile app.
We currently host PRS and EARS on Azure as they are .Net apps, but we are currently porting these services to Scala and will be hosting them on Heroku with the other P2 SRX services.
Serviço utilizado para deploy de toda a infraestrutura do projeto. Colocamos todas as peças do serviço no azure, garantindo uma forma rápida e garantia de escalibilidade.
Blackbaud makes use of Azure and my current job is with Blackbaud. Therefore, due to the free credit and the ability to reuse tools, I rely on Azure quite a bit.
Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.