AWS vs. Azure vs. Google: Cloud Comparison

The three leading cloud computing vendors, AWS, Microsoft Azure and Google Cloud, each have their own strengths and weaknesses that make them ideal for different use cases.


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In the public cloud computing market, three vendors dominate: Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). When it comes to infrastructure as a service (IaaS) and platform as a service (PaaS), these three have a huge lead on the rest of the field.

Amazon is particularly dominant. In a Q3 2017 report, Synergy Research Group noted that "Microsoft, Google and Alibaba are all growing their revenues much more rapidly than Amazon and they continue to gain market share, but the reality is that in this market Amazon remains bigger than its next five largest competitors combined."

How exactly do AWS, Azure and GCP differ? Read our overview below, or see user reviews:

AWS vs. Azure vs. Google: Overall Pros and Cons

Many experts recommend that enterprises evaluate their public cloud needs on a case-by-case basis and match specific applications and workloads with the vendor that offers the best fit for their needs. Each of the leading vendors has particular strengths and weaknesses that make them a good choice for certain projects.

AWS pros and cons

Amazon's biggest strength is its dominance of the public cloud market. In its June 2017 Magic Quadrant for Cloud Infrastructure as a Service, Worldwide Gartner noted, "AWS has been the market share leader in cloud IaaS for over 10 years."

Part of the reason for its popularity is undoubtedly the massive scope of its operations. AWS has a huge and growing array of available services, as well as the most comprehensive network of worldwide data centers. The Gartner report summed it up, saying, "AWS is the most mature, enterprise-ready provider, with the deepest capabilities for governing a large number of users and resources."

Amazon's big weakness relates to cost. While AWS regularly lowers its prices, many enterprises find it difficult to understand the company's cost structure and to manage those costs effectively when running a high volume of workloads on the service.

In general, however, these cons are more than outweighed by Amazon's strengths, and organizations of all sizes continue to use AWS for a wide variety of workloads.

Microsoft Azure pros and cons

Microsoft came late to the cloud market but gave itself a jump start by essentially taking its on-premises software – Windows Server, Office, SQL Server, Sharepoint, Dynamics Active Directory, .Net, and others – and repurposing it for the cloud.

A big reason for Azure’s success has to do with the fact that so many enterprises deploy Windows and other Microsoft software. Because Azure is tightly integrated with these other applications, enterprises that use a lot of Microsoft software often find that it also makes sense for them to use Azure. This builds loyalty for existing Microsoft customers. Also, if you are already an existing Microsoft enterprise customer, expect significant discounts off service contracts.

On the con side, Gartner finds fault with some of the platform's imperfections. "While Microsoft Azure is an enterprise-ready platform, Gartner clients report that the service experience feels less enterprise-ready than they expected, given Microsoft's long history as an enterprise vendor," it said. "Customers cite issues with technical support, documentation, training and breadth of the ISV partner ecosystem."

In addition, Gartner said that Azure doesn't offers as much support for DevOps approaches as some of the other cloud platforms. For example, it doesn't have as much integrated automation, requiring staff to perform many management tasks by hand.

Google Cloud Platform pros and cons

Google has a strong offering in containers, since Google developed the Kubernetes standard that AWS and Azure now offer. GCP specializes in high compute offerings like Big Data, analytics and machine learning. It also offers considerable scale and load balancing – Google knows data centers and fast response time.

On the downside, Google is a distant third in market share, perhaps because it doesn't offer as many different services and features as AWS and Azure. It also doesn't have as many global data centers as AWS or Azure, although it is quickly expanding.

Gartner said that its "clients typically choose GCP as a secondary provider rather than a strategic provider, though GCP is increasingly chosen as a strategic alternative to AWS by customers whose businesses compete with Amazon, and that are more open-source-centric or DevOps-centric, and thus are less well-aligned to Microsoft Azure."

aws vs. azure vs. google, cloud compare

AWS vs. Azure vs. Google: Compute

AWS Compute:

  • Elastic Compute Cloud: Amazon's flagship compute service is Elastic Compute Cloud, or EC2. Amazon describes EC2 as "a web service that provides secure, resizable compute capacity in the cloud." EC2 offers a wide variety of options, including a huge assortment of instances, support for both Windows and Linux, bare metal instances (currently a preview), GPU instances, high-performance computing, auto scaling and more. AWS also offers a free tier for EC2 that includes 750 hours per month of t2.micro instances for up to twelve months.

  • Container services: Within the compute category, Amazon's various container services are increasing in popularity, and it has options that support Docker, Kubernetes, and its own Fargate service that automates server and cluster management when using containers. It also offers a virtual private cloud option known as Lightsail, Batch for batch computing jobs, Elastic Beanstalk for running and scaling Web applications, as well as a few other services.

Microsoft Compute:

  • Virtual Machines: Microsoft's primary compute service is known simply as Virtual Machines. It boasts support for Linux, Windows Server, SQL Server, Oracle, IBM, and SAP, as well as enhanced security, hybrid cloud capabilities and integrated support for Microsoft software. Like AWS, it has an extremely large catalog of available instances, including GPU and high-performance computing options, as well as instances optimized for artificial intelligence and machine learning. It also has a free tier with 750 hours per month of Windows or Linux B1S virtual machines for a year.

  • Additional Services: Azure's version of Auto Scaling is known as Virtual Machine Scale Sets. And it has two container services: Azure Container Service is based on Kubernetes, and Container Services uses Docker Hub and Azure Container Registry for management. It has a Batch service, and Cloud Services for scalable Web applications is similar to AWS Elastic Beanstalk. It also has a unique offering called Service Fabric that is specifically designed for applications with microservices architecture.

Google Compute:

  • Compute Engine: By comparison, Google's catalog of compute services is somewhat shorter than its competitors'. Its primary service is called Compute Engine, which boasts both custom and predefined machine types, per-second billing, Linux and Windows support, automatic discounts and carbon-neutral infrastructure that uses half the energy of typical data centers. It offers a free tier that includes one f1-micro instance per month for up to 12 months.

  • Focus on Kubernetes: Google also offers a Kubernetes Engine for organizations interested in deploying containers. And it's worth noting that Google has been heavily involved in the Kubernetes project, giving it extra expertise in this area.

aws vs. azure vs. google, cloud compare,compute services

AWS vs. Azure vs. Google: Storage

AWS Storage:

  • SSS to EFS: AWS offers a long list of storage services that includes its Simple Storage Service (S3) for object storage, Elastic Block Storage (EBS) for persistent block storage for use with EC2, and Elastic File System (EFS) for file storage. Some of its more innovative storage products include the Storage Gateway, which enables a hybrid storage environment, and Snowball, which is a physical hardware device that organizations can use to transfer petabytes of data in situations where Internet transfer isn't practical. .

  • Database and archiving On the database side, Amazon has a SQL-compatible database called Aurora, Relational Database Service (RDS), DynamoDB NoSQL database, ElastiCache in-memory data store, Redshift data warehouse, Neptune graph database and a Database Migration Service. Amazon doesn't offer a backup service, per say, however, it does have Glacier, which is designed for long-term archival storage at very low rates. In addition, its Storage Gateway can be used to easily set up backup and archive processes .

Azure Storage:

  • Storage Services: Microsoft Azure's basic storage services include Blob Storage for REST-based object storage of unstructured data, Queue Storage for large-volume workloads, File Storage and Disk Storage. It also has a Data Lake Store, which is useful for big data applications. .

  • Extensive Database: Azure's database options are particularly extensive. It has three SQL-based options: SQL Database, Database for MySQL and Database for PostgreSQL. It also has a Data Warehouse service, as well as Cosmos DB and Table Storage for NoSQL. Redis Cache is its in-memory service and the Server Stretch Database is its hybrid storage service designed specifically for organizations that use Microsoft SQL Server in their own data centers. Unlike AWS, Microsoft does offer an actual Backup service, as well as Site Recovery service and Archive Storage .

Google Storage:

  • Unified Storage and more: As with compute, GCP has a smaller menu of storage services available. Cloud Storage is its unified object storage service, and it also has a Persistent Disk option. It offers a Transfer Appliance similar to AWS Snowball, as well as online transfer services.

  • SQL and NoSQL When it comes to databases, GCP has the SQL-based Cloud SQL and a relational database called Cloud Spanner that is designed for mission-critical workloads. It also has two NoSQL options: Cloud Bigtable and Cloud Datastore. It does not have backup and archive services .

aws vs. azure vs. google, cloud compare, storage

AWS vs. Azure vs. Google: Key Cloud Tools

Looking ahead, experts say that emerging technologies like artificial intelligence, machine learning, the Internet of Things (IoT) and serverless computing will become key points of differentiation for the cloud vendors. All three leading vendors have begun experimenting with offerings in these areas and are likely to expand their services in the coming year.

AWS Key Tools:

  • Pagemaker to Serverless: As in other areas, AWS has the longest lists of services in each of these areas. Highlights include its SageMaker service for training and deploying machine learning models, the Lex conversational interface that also powers its Alexa services, its Greengrass IoT messaging service and the Lambda serverless computing service. .

  • AI and ML: At its 2017 re:Invent show, Amazon introduced a number of AI-oriented services as well. It launched DeepLens, an AI powered camera for for developing and deploying machine learning algorithms to use with things like optical character recognition and image and object recognition. AWS has announced Gluon, an open source deep learning library designed to make it easy for developers and non-developers alike to build and quickly train neural networks without having to know AI programming..

Azure Key Tools:

  • Cognitive Services: Microsoft has also invested heavily in artificial intelligence, and it offers a machine learning service and a bot service on Azure. It also has Cognitive Services that include a Bing Web Search API, Text Analytics API, Face API, Computer Vision API and Custom Vision Service. For IoT, it has several management and analytics services, and its serverless computing service is known as Functions. .

  • Supporting MSFT Software Not surprisingly, many of Azure’s top tools are geared around supporting on-premises Microsoft software. Azure Backup is a service that links Windows Server Backup in Windows Server 2012 R2 and Windows Server 2016. Visual Studio Team Services hosts Visual Studio projects on Azure .

Google Key Tools:

  • Big on AI: For Google Cloud Platform, AI and machine learning are big areas of focus. Google is a leader in AI development thanks to TensorFlow, an open source software library for building machine learning applications. The library is popular since it is open source and is widely used. A testament to its popularity is that AWS recently added support for TensorFlow.

  • IoT to Serverless: Google Cloud has strong offerings in APIs for natural language, speech, translation and more. Additionally, it offers IoT and serverless services, but both are still in beta previews .

aws vs. azure vs. google, cloud compare, advanced cloud tools

AWS vs. Azure vs. Google: Pricing

Also see: an in-depth look at AWS vs. Azure vs. Google pricing for cloud services.

When comparing the three cloud leaders, pricing is sometimes the trickiest area of all. Yet it is possible to make some generalizations.

  • AWS Pricing: Amazon's pricing is particularly inscrutable. While it does offer a cost calculator, the many number of variables involved make it difficult to get accurate estimates. Gartner advised, "[Amazon's] granular pricing structure is complex; use of third-party cost management tools is highly recommended."

  • Azure Pricing: Microsoft Azure doesn't make things any simpler. Because of Microsoft's complicated software licensing options and use of secretive discounts, its pricing structure can be even more difficult to understand without outside help.

  • Google Pricing: By contrast, Google uses its pricing as a point of differentiation. It aims to offer "customer-friendly" prices that beats the list prices of the other providers. Gartner noted, "Google uses deep discounts and exceptionally flexible contracts to try to win projects from customers that are currently spending significant sums of money with cloud competitors."

Key tip: Organizations that are basing their cloud vendor decisions primarily on price will need to analyze each project on a case-by-case basis to get the best deal. And because the vendors drop their prices regularly, they may need to revisit those calculations frequently.

AWS vs. Azure vs. Google: What’s Best for You?

As noted in the beginning of this article, the best public cloud vendor for you is going to depend on your needs and your workloads. In fact, the best vendor for some of your projects might not be the best vendor for others of your projects. Many experts believe that the majority of enterprises will pursue a multi-cloud strategy in the near future either in an effort to prevent vendor lock-in or in an effort to match workloads with the best available service.

  • The AWS Choice: You can’t go wrong with AWS due to its rich collection of tools and services and massive scale. The only reason not to choose Amazon is if you want a more personal relationship, something a small boutique shop can offer. At its size, it’s hard for Amazon to have a close relationship with every customer, but there are resellers and consultants who can offer that type of attentive focus.

  • The Azure Choice: Microsoft’s greatest appeal is, of course, to Microsoft shops. All of your existing .Net code will work on Azure, your Server environment will connect to Azure, and you will find it easy to migrate on-premises apps. If you want Linux, DevOps, or bare metal, however, Microsoft would not be the ideal choice. It offers Linux but it takes a back seat in priority to Windows. DevOps is primarily a Linux/open source play, again, something Microsoft does not specialize in.

  • The Google Choice: Google is growing quickly but is a work in progress. Its offerings were meager and it didn’t have a legacy background in dealing with businesses. But it is fully committed and plowed billions into its cloud efforts. And it is partnered with Cisco, which does know the enterprise. The people who should look at Google now are the ones who looked a year ago and didn’t like what they saw. They might be surprised. Google has built its cloud on its strength, which is scale and machine learning. it’s clearly worth a look.

Bottom line: Certain types of companies will be more attracted to certain cloud vendors. So again, if your firm runs Windows and a lot of Microsoft software, you'll probably want to investigate Azure. If you are a small, Web-based startup looking to scale quickly, you might want to take a good look at Google Cloud Platform. And if you are looking for the provider with the broadest catalog of services and worldwide reach, AWS will probably be right for you.

AWS vs. Azure vs. Google: Vendor Pages

The following are links to the AWS's, Azure's and Google's own pages about a variety of tools, from compute to storage to advanced tools:



Amazon Web Services

Microsoft Azure

Google Cloud Platform


Global Infrastructure


Regions and Zones


Cloud Services Pricing



Basic Compute


Virtual Machines

Compute Engine





Container Instances

Kubernetes Engine




Cloud Functions

App Hosting

Elastic Beanstalk

App Service

Service Fabric

Cloud Services

App Engine

Batch Processing




Object Storage


Blob Storage

Cloud Storage

Block Storage



Persistent Disk

File Storage


File Storage


Hybrid Storage

Storage Gateway



Offline Data Transfer


Snowball Edge



Transfer Appliance


Relational/SQL Database



SQL Database

Database for MySQL

Database for PostgreSQL

Cloud SQL

Cloud Spanner

NoSQL Database


Cosmos DB

Table Storage

Cloud Bigtable

Cloud Datastore

In-Memory Database


Redis Cache






Disaster Recovery


Site Recovery


Machine Learning



Apache MXNet on AWS

TensorFlow on AWS

Machine Learning

Cloud Machine Learning Engine

Cognitive Services







Cognitive Services

Cloud Natural Language

Cloud Speech API

Cloud Translation API

Cloud Video Intelligence


IoT Core

IoT Hub

IoT Edge

Cloud IoT Core


Direct Connect

Virtual Network

Cloud Interconnect

Network Service Tiers

Content Delivery



Cloud CDN

Big Data Analytics





Stream Analytics

Data Lake Analytics

Analysis Services

Cloud Dataflow

Cloud Dataproc

Authentication and Access Management


Directory Service


Single Sign-On

Active Directory

Multi-Factor Authentication

Cloud IAM

Cloud IAP






Security Center

Cloud DLP

Cloud Security Scanner


Application Lifecycle Management



Visual Studio Team Services

Visual Studio App Center


Cloud Monitoring




Log Analytics


Cloud Management

Systems Manager

Management Console



Cost Management






Virtual Private Cloud



Virtual Private Cloud


Training and Certification


Training Programs





3rd Party Software and Services



Cloud Launcher

Partner Directory


Tags: AWS, Cloud, Azure, AI, machine learning, Google Cloud, IoT

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