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Azure vs. Google: Cloud Compare

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In the fierce battle for cloud market share, Microsoft Azure and Google Cloud Platform are clearly two of the top cloud companies. Both companies offer an extensive menu of sophisticated cloud tools, and both have exceptionally deep pockets to continually build out their public cloud platform. 

Google got the head start by almost two years. It launched Google Cloud Platform (GCP) in 2008, just two years after Amazon and two years before Microsoft launched Windows Azure (before rebranding it Microsoft Azure in 2014).

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But Microsoft has the lead: Synergy Research Group puts Microsoft in second place among cloud companies at about 14% share, while GCP is in fourth place with just 6% market share. Amazon Web Services leads with 34% market share; in third is IBM Cloud at 7%.

Cloud Resources:

Azure vs. Google: Summary

Azure and Google Cloud could hardly be more different in the cloud space. Microsoft made a masterful pivot to the cloud, a move that began under Steve Ballmer but took off under the solid leadership of Satya Nadella. Its cloud platform benefits from Microsoft’s deep legacy investment in the enterprise. Windows has been the bedrock of corporate computing for decades – so it’s no surprise that Azure fits enterprise needs so well. 

Google was born online, lives online and makes almost nothing on-premise (except for the Chrome browser). Internet search, of course, is Google’s greatest strength, and the deep-geek algorithms of search have little to do with the personal glad-handing of enterprise sales reps. In short, tech insiders often note that “the enterprise simply isn’t in Google’s DNA.”

Azure leads Google Cloud because (among other reasons) Microsoft has masterfully leveraged its enterprise smarts and on-premise data center legacy to migrate customers to Azure, while Google spent too much time as a pure cloud play when customers overwhelmingly want a hybrid cloud. Google seemed to think that businesses would go all-in to the cloud and that hasn’t happened just yet.

But Google has a few unique elements that make it a cloud computing company worth keeping in mind by any potential customer. In particular, Google Cloud’s profound expertise in metrics, data analytics, artificial intelligence and machine learning offer crucial competitive advantage. Google remains very invested in pushing its cloud platform forward aggressively.

Also see: AWS vs. Azure vs. Google: Cloud Comparison [2019 Update]

Azure vs. Google: The Core Platforms

Both cloud vendors, of course, offer the core cloud tools, including containers and microservices, Big Data, DevOps, and databases. But they differ, too. So let’s break it down.

Microsoft Azure: The Basics

Azure also has four classes of offerings with a slight variation:

  • Data management/databases
  • Compute
  • Networking
  • Performance

Security and management is done through Microsoft’s Active Directory, which is built on the very mature Active Directory services first introduced into Windows Server 2000. These include:

  • Active Directory Federation Services
  • Azure Active Directory
  • Multi-Factor Auth
  • Role Based Access for cloud-based security

Google Cloud: The Basics

GCP breaks down into five specific services:

  • Computing and hosting
  • Storage
  • Networking
  • Big data
  • Machine learning

For PaaS, Google has Google App Engine, which allows for much greater scalability of its apps than AWS, but is limited in languages and operating environments. AWS supports Windows and open source, while GCP is focused on NIX and open source languages.

For basic IaaS, there is Google Compute Engine, which is a typical IaaS offering for rapid deployment of virtual machines. However, Google has a few advantages. It charges far less per virtual machine than any other provider and has much more fine-grained billing, down to the second, rather than the minute for AWS.

Microsoft Azure Pro and Con

Azure offers the gamut of SaaS, IaaS, and PaaS services, along with Azure App Services for migrating your Windows environment. Microsoft offers a variety of models:

• Free Tier (F1): run up to 10 apps for free in a shared instance.

• Shared (S1): fixed per-hour with SSL and custom domain, with up to 100 apps.

• Basic (B1–B3): dedicated instances with 99.95% uptime SLA.

• Standard (S1–S3): Basic plus scale out support, daily backups and deployment slots.

• Premium (P1–P4): Dedicated App Service Environments (ASEs) for private network space.

Azure’s major advantage over all of its competition is the Microsoft enterprise legacy. From the beginning, Microsoft made it very easy to migrate your on-premises Microsoft environment to Azure, starting with a free, basic discovery and assessment tool called Azure Migrate. Azure Migrate evaluates your on-premises environment and provides a visual map of interdependencies among servers to identify multi-tier applications.

Azure Migrate also tells you if your on-premises app is suitable for migrating to an Azure virtual machine or if it needs modification and provides an estimate of the proper size and cost of the Azure virtual environment for the app to run properly.

For web apps, Microsoft provides the Windows Site Migration Tool, which can migrate an entire site, content and all, dating back to Internet Information Server (IIS) 5 and Windows Server 2003. There is also a Linux Site Migration Tool for moving Apache-based sites to Azure.

Azure and Developers

To support app development, Azure has multiple app deployment options for developers:

• App Services, a fully managed Platform as a Service

• Cloud Services for deploying Web apps and APIs

• Service Fabric for building microservices

• Kubernetes Service for deploying container services

• Functions, an architecture for serverless and IAC

• Batch job scheduling

Hybrid Cloud

Deploying a hybrid environment is much easier with Azure because Microsoft recognized the need for a hybrid environment from the beginning. In addition to Azure, Microsoft lets you turn your on-premises servers into an Azure environment with Azure Stack. Azure Stack lets you duplicate an Azure environment within your own data center and firewall, using the same services internally, and being able to seamlessly move and migrate apps between your premises and the Azure cloud.

This allows you to utilize cloud-based resources on-site when necessary. It appeals primarily to highly regulated industries where data might have to stay on-site rather than be moved to the cloud.

As for negatives to Azure, some say it doesn’t offer as much support for DevOps development methods as other cloud platforms. Its dev tools are geared to the Microsoft method of development, though surely there are plenty of Microsoft shops that are undoubtedly good with that.

Azure isn’t a Microsoft-only environment. The company points out that a third of its customers use Linux and it offers multiple flavors of Linux instances. And while Microsoft does support many open source initiatives like Hadoop and Kubernetes, Google was born of open source software and in some ways is much further along.

Also, with Microsoft, licensing gets a bit complicated when it comes to apps and servers. If you have Microsoft licenses, you might be eligible for license mobility to move to the cloud, so you don’t have to pay for both the on-prem and cloud version. This will require some work on your part with your consultants/MVPs.

Google Cloud Pro and Con

Google was born of the cloud and is almost entirely a cloud play with little on-prem support. That’s one reason why it’s playing catch-up with AWS and Microsoft. GCP offers a number of IaaS/PaaS services, starting with compute:

• Compute Engine

• App Engine

• Kubernetes Engine

• GKE On-Prem – to make apps cloud-ready and move them to the cloud.

• Cloud Functions – serverless computing

• Knative – components to create Kubernetes-native cloud-based software.

• Shielded VMs – Hardened virtual machines on GCP.

• Container Security It also has quite a collection of developer tools, all of which are open source in origin if not home grown.

• Cloud SDK

• Container Registry

• Cloud Build – DevOps continuously build, test, and deploy.

• Cloud Source Repositories – A single place for your team to store, manage, and track code.

• Firebase Crashlytics Logging and monitoring is provided to monitor the performance and availability of your resources and applications via Stackdriver Logging, which collects and stores logs from applications and services running on Cloud Platform, and Stackdriver Monitoring, which provides dashboards and alerts for your applications.


For DevOps, Google has three main tools:

Google Compute Engine, the main service which allows users to launch virtual machines on demand. Compute Engine’s VMs boot quickly, comes with persistent disk storage, and delivers consistent performance.

GCP Deployment Manager, for defining all of the resources needed for your application.

GCP Cloud Console offers a dashboard with a detailed view of every detail of your DevOps in the cloud, like the apps, virtual machines, datastore, databases, networking, and developer services.


An area of strength for Google is its support for Kubernetes orchestration. Google invented Kubernetes and is on top of development, even though it has turned management of the spec to the Cloud Native Computing Foundation.

Google Container Engine (GKE) is GCP’s managed Kubernetes service, which features load balancing and global spanning, an advantage unique to Google. Azure’s load balancer is just another container instance you need to scale. You can also add or upgrade nodes through the GCP console.

Microsoft was late to Kubernetes but it does support it through the Azure Container Service (ACS). It doesn’t have the best management or automation, but it does create templates out of your infrastructure very easily.

Many of the strengths of GCP originate with the Google search engine and its basic services. Google has a massive worldwide presence and is constantly building new data centers all over the globe. GCP has what is called multi-regional deployment mode, so you can deploy your site in multiple regions for the fastest response times.

Google’s billing is considered much more customer friendly, with lower costs than the competition, discounts for long-running workloads and no up-front commitment required. Azure, on the other hand, requires full up-front payment in some cases. Azure billing is considered more confusing, especially with on-premises licensing, although Microsoft does have a bill monitoring service.


In addition to the infrastructure, Google – of course – has an unmatched network of fiber connections making its backbone faster than the Internet in some ways. It has cables between the U.S. and Europe and Asia with multi terabits of bandwidth. It is the only cloud provider with a tiered cloud network of standard and premium, so you can use Google’s network for best performance.

Google’s greatest strength is its commitment to artificial intelligence and machine learning. Google has invested heavily in its own AI chip, called the Tensor Processing Unit (TPU). The TPU is not for sale and only available as a service on GCP. It is specifically designed for machine learning and is used by several Google services, including Translate, Gmail, and Search.

Google offers Cloud Machine Learning for general purpose machine learning and specific uses based on its services. It has APIs for Cloud Vision, Cloud Speech, Cloud Natural Language and Google Translate, which are based on the image recognition, speech recognition, speech to text and foreign language translations, respectively.

Azure vs. Google Strengths at a Glance

Azure Google Compute Engine
OS Linux, Windows Linux, Windows
Storage Block, Object Block, Object
Tiered networking No Yes
DevOps Yes Yes
Data center regions 54 18
Billing Per second Per second
Billing calculator Yes Yes
Containers Kubernetes Kubernetes
Strengths • Total support for Microsoft legacy apps
• Easy one-click migrations in many cases
• Conversion of on-prem licenses to the cloud
• Good support for mixed Linux/Windows environments
• Better hybrid cloud offering
• Better support for disaster recovery
• Top Kubernetes support
• Better DevOps support
• Heavy involvement in AI
• Simpler licensing
• Faster private network for low latency
• Better load balancing globally

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