The competition for leadership in the public cloud computing is fierce three-way race between AWS vs Azure vs Google.
Clearly, for infrastructure as a service (IaaS) and platform as a service (PaaS), Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) hold a commanding position among the many cloud companies.
Amazon is particularly dominant. According to a 2020 report from Synergy Research Group, “Amazon growth continued to closely mirror overall market growth so it maintained its 33% share of the worldwide market. Second ranked Microsoft again grew fast than the market and its market share has increased by almost three percentage points in the last four quarters, reaching 18%.”
Here’s the summary cloud comparison between AWS vs. Azure vs. Google:
- Amazon Web Services – With a vast tool set that continues to grow exponentially, Amazon’s capabilities are unmatched. Yet its cost structure can be confusing, and its singular focus on public cloud rather than hybrid cloud or private cloud means that interoperating with your data center isn’t AWS’s top priority.
- Microsoft Azure – A close competitor to AWS with an exceptionally capable cloud infrastructure. If you’re an enterprise customer, Azure speaks your language – few companies have the enterprise background (and Windows support) as Microsoft. Azure knows you still run a data center, and the Azure platform works hard to interoperate with data centers; hybrid cloud is a true strength.
- Google Cloud – A well-funded underdog in the competition, Google entered the cloud market later and doesn’t have the enterprise focus that helps draw corporate customers. But its technical expertise is profound, and its industry-leading tools in deep learning and artificial intelligence, machine learning and data analytics are significant advantages.
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 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: 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.”
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: 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: Among its many AI-oriented services, AWS offers 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 TensoreFlow library is popular and well regarded. 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.