AWS vs. Azure vs. GCP: A Comparison of Cloud Platforms

Worldwide Revenues

AWS, an Amazon subsidiary for over 20 years in the market and the highest revenue in the industry, offers metered pay-as-you-go, on-demand cloud computing platforms and APIs to individuals, companies, and governments, continuously taking a third of the worldwide revenue.

Azure, operated by Microsoft since 2008, offers similar services via the Wide World Web, is the second most profitable in the market and gradually becoming a major competitor for AWS. It helps companies and individuals by building, running, and managing software apps and tools across different clouds.

GCP, considered the youngest in the Google Cloud vs AWS vs Azure contrast, was launched the same year as Azure but has been actually generally available only since 2011. It provides a robust assemblage of cloud services that can run and support any application.

Market Size

The market for cloud computing has been expanding quickly in recent years and is predicted to grow further in the years to come. A report from Grand View Research states that with a forecasted compound annual growth rate (CAGR) OF 14.1 from 2023 to 2030, the global cloud computing market, which was estimated at USD 483.98 billion in 2022, will develop at a faster pace than average.

Pay-as-you-go SaaS-based business models and the functional ability of cloud computing to improve business performance are some of the major factors that are anticipated to fuel this market growth.

According to Statista, the cloud platforms that make up the global share market for cloud computing services are Amazon (AWS), Microsoft Azure, Google Cloud, Alibaba Cloud, and IBM Cloud. Among all of these, there are three platforms that make up most of the market and the subject of this article.

Thus, in terms of this cloud platform comparison, at the top, with the highest market share, there is AWS, which has been controlling about 32% of the industry for the couple last years. Microsoft Azure takes the second place in the leading board with over 23% of the market share. Lastly, GCP, among the three, comes in third with just under 10%, so far. Altogether, they account for 65% – almost two-thirds – of the total cloud computing market share.

Global Infrastructure

Cloud providers deliver their services over the high-bandwidth global fiber network that spans across oceans and continents. This network connects multiple physical data centers housing the servers that provide storage and computing capacity to cloud services users. A set of data centers that are interconnected through a dedicated low-latency network and deployed within a certain latency-defined perimeter make up a region. Each region falls under a specific pricing and service availability offering.

Within a service region, cloud providers distinguish physically separated availability zones consisting of one to several data centers that guarantee the availability of users’ data and services in case of unforeseen failures. Another part of the global cloud infrastructure are the Points of Presence (PoPs) – physical locations and access points at the edge or intersection of networks that ensure network accessibility, performance, and redundancy for the optimal delivery of cloud services, including edge locations and data centers.

In the table below, we summarize the numbers that reflect the AWS vs Azure vs GCP comparison of infrastructures.

*as of 2020, no current data
** three Availability Zones per supported Azure region
– no current data

Amazon Web Services currently cover 102 Availability Zones in 32 Geographic Regions across the Americas, Africa, Europe, Middle East, Asia, and Oceania, promising to further expand. This includes 245 countries and territories, which is also the highest number of served areas in the Azure, AWS, and Google comparison.

Azure provides its services in more than 60 Azure regions around the globe that comprise over 300 physical data centers, and over 185 points of presence, compared with Amazon’s 600. As of January 2020, Amazon was known to have a presence in 140 countries around the world.

Google Cloud Platform claims availability in more than 200 countries and territories and is actively expanding its network. GCP offers its coverage in 39 regions and 118 zones, almost every region including three zones.

Cloud Service Models

Before we move on to discussing the service offerings from AWS, Azure, and GCP, here’s a quick reminder about the cloud service delivery models for our readers:

• Software as a Service (SaaS) is a software licensing model that allows users to access the software on a subscription basis using external servers. Typically, SaaS products are ready-to-use, intuitive, user-facing applications with no or relatively low learning curve, fully managed by the provider.Examples of cloud SaaS offerings include Amazon WorkMail, Microsoft’s Office 365, and Outlook or Google Workspace and Google Drive.
• Platform as a Service (PaaS) is a cloud computing model that provides a complete cloud platform – hardware, software tooling, and infrastructure – for users to develop, run, and manage applications without the cost, flexibility issues, and complexity of maintaining such a platform themselves. The PaaS userbase will be software developers with the skills and knowledge required to use the tooling to create software applications.
  Some examples of PaaS are AWS Lambda, Azure Service Bus, or Google’s Cloud Run and App Engine.
• Infrastructure as a Service (IaaS) is a type of cloud computing service that provides clients with the needed IT infrastructure, such as computing, storage, and networking on demand, usually on a pay-per-use basis. Under this service provision model, the cloud provider manages the infrastructure while the user, usually a company with plenty of resources, remains responsible for handling the deploying, maintaining, and supporting of their apps.
  Amazon EC2, Azure Virtual Machines, and Google Compute Engine are some of the most prominent examples of IaaS offerings from the top three cloud providers.

All of the cloud service providers in question try to stay innovative and competitive, continuously rolling out new offers and services complementing their existing stack. So, questions like “AWS vs Azure vs GCP, which is better” may arise. To answer that, further we discuss the Azure vs Google vs Amazon service offerings and find out the strengths and weaknesses of each cloud provider.

Cloud Computing Services

A variety of popular computing services, such as virtual machines, containers, and serverless computing, are provided by all of The Big Three cloud providers. Recognized as Gartner Magic Quadrant Leader for Cloud Infrastructure and Platform Services for twelve years in a row, AWS offers the broadest range of cloud computing choices, with a selection of instance types and sizes. Similar services are provided by Azure, which is more well-liked by companies that use Microsoft’s products due to its smooth integration. Kubernetes and other open-source technologies are well supported by GCP, which is renowned for its user-friendly UI.

Artificial Intelligence (AI) and Machine Learning (ML) Workloads

All three companies offer many AI and ML services for application development, including speech recognition, speech synthesis, natural language processing, computer vision, data extraction, and more. Amazon’s SageMaker and Rekognition are only two of the many AI and ML application development services that AWS provides. Azure offers comparable services, such as Azure Machine Learning and Cognitive Services. Cloud AI Platform and Cloud Vision API are two of the AI and ML services provided by GCP.

Generative AI

With the arrival of OpenAI’s ChatGPT, generative AI has become a must-have technology in many modern solutions. To satisfy clients’ needs in this domain, AWS offers Amazon Bedrock – a service providing access to multiple Fully Managed Models for creating apps with text and image generation functionality avoiding the need to take care of infrastructure management. At their last event, they also presented AmazonQ – a generative AI-powered assistant, and PartyRock – a sharable playground for Amazon Bedrock.

Azure has certainly benefited from OpenAI’s pioneering in this market, serving as OpenAI’s exclusive cloud provider with its Azure OpenAI Service. GCP is not falling far behind, having rolled out the enterprise-ready Vertex AI technology for work with Large Language Models (LLMs).

Below, you can find the comparison of AWS, Azure, and Google Cloud offerings arranged into a table, taking into consideration pricing and the most popular services, such as integration services, storage, networking, security, and developer tools.

This AWS, GCP, and Azure comparison shows that all three provide an extensive range of cloud-based services that their customers can benefit from. Most of them have decent alternatives across different platforms. But one should remember that in some cases, certain services may not be available depending on the country or region, so stay alert for location-specific offerings of cloud providers and pick the one that will definitely be closer to your users.

In the following section, we’ll proceed with the Azure, AWS, and Google comparison, concentrating on each cloud provider’s strong and weak sides.

Pros of AWS

• Market Prevalence
  As we’ve outlined previously, AWS has been there for a longer time and has gained one-third of the global cloud services market. This makes it a more experienced and confident player with a well-built brand name, extensive infrastructure worldwide, and a quantitative advantage over the competitors.
• Maturity
  Of the three cloud providers in question, AWS has been in the cloud solutions market for the longest and has an established reputation. This also means it’s infrastructure and services are time-tested and reliable while its business partnerships can last for decades.
• Service Range
  Currently, Amazon Web Services can provide its users with over 200 solutions and services for storage, networking, data analytics, cloud computing, and cloud-native development. This includes service offerings for low-latency solutions, on-premises applications, public sector and highly regulated domains, and even satellite communications.
• Coverage
  AWS claims to have the largest cloud infrastructure among cloud service providers, with the most data centers and PoSs around the globe. They are also known to have the largest amount of hyperscale data centers. An extensive infrastructure allows to deploy your AWS cloud apps as close to your users as possible, delivering high performance and minimal latency.
• Serverless Computing
  While all three cloud service providers offer multiple tools for serverless computing, AWS Lambda remains the top choice of software engineers as the most established and mature technology. It is also preferred for its flexible pricing, wide language adoption, and auto-scaling based on workload changes.

Cons of AWS

• Country Limitations
  AWS is limited to certain countries. Since Amazon is based in the United States, each service promoted may not be accessible or limited by default in certain countries.
• Complex Pricing
  A rather general problem, with flexible and pay-per-need billing models, comes the complexity of keeping track of all the resources actually used, which gets even harder with regional discrepancies.

However, such drawbacks can be easily mitigated with the support and guidance of qualified specialists providing AWS consulting services.

Among the companies that use AWS based on EC2, there are giants that spend between $8 to $20 million in monthly expenses:

• Netflix
• LinkedIn
• Facebook
• ESPN

Pros of Azure

• Hybrid Cloud Focus
  Unlike AWS and GCP, Azure is known to pay a lot of attention to supporting hybrid cloud environments. This is particularly beneficial for customers from highly regulated domains who need to keep some part of their infrastructure on-premises. Potential cloud users willing to migrate from on-prem gradually will also appreciate high-quality hybrid cloud services.
• Microsoft Ecosystem
  As we’ve already mentioned, Azure Cloud provides its clients with smooth integration with other Microsoft solutions and services, which makes your entire infrastructure manageable with a single Microsoft account. This particularly appeals to large enterprise customers with established business relationships with the company.
• ML and AI
  Azure is the exclusive OpenAI partner providing access to the Azure OpenAI Service for its customers. Azure’s ML services also include a complete toolset for building AI-powered solutions, from low-code to advanced developer tooling. And of course, we cannot avoid mentioning GitHub Copilot developed in collaboration with OpenAI – the pioneer generative AI-powered coding assistant which has been around for a while.
• Compliance
  Azure is often the top choice for heavily regulated domains not only because its attention to customers with on-premise infrastructure. It also has a broad range of compliance certifications, meeting the regulatory requirements of various industries.
• IDE
  Microsoft’s Visual Studio is known to be many software engineers’ favorite for the support of multiple programming languages and extensive functionality that allows one to complete an entire SDLC in one place. It is also integrated with Azure’s ML development toolset, providing even more flexibility and creative opportunities.

Cons of Azure

• Management Complexity
  As with any large-scale solution, Azure infrastructure requires specialized management and upkeep, including full-time resource monitoring and optimization. Therefore, it is essential to get proper expertise, in-house or outsourced at a digital transformation company, to handle the platform’s infrastructure efficiently.
• Vendor Lock-In
  A benefit for businesses whose needs can be fully satisfied by Microsoft’s ecosystem, this turns into a stumbling stone if you come to realize that other provider’s tools or services will work better in your scenario. You might consider going for a multi-cloud strategy to avoid such a situation.

Azure is most often chosen by large-scale products and companies. Here are some of the companies that rely on Azure’s cloud infrastructure:

• Shell
• eBay
• Johnson & Johnson
• Honeywell
• Dell

Pros of GCP

• Big Data Processing
  Google has a long-standing experience in processing big data gaining valuable insights from it based on a variety of variables, including search history, location tracking, user behavior tracking, etc. Given that big data is one of GCP’s main strong fields of expertise, it has a variety of cutting-edge tools for cloud warehousing as well.
• ML and AI
  The creator of the Text-to-Speech and Speech-to-Text solutions that were the first of their kind, GCP is particularly strong and experienced in the field of natural language processing, voice recognition, and image recognition and continues to deepen this expertise.
• Robust Security
  GCP is known to pay great attention to physical and informational security for their users’ applications with a range of backup, security, and identity services, including Identity and Access Management (IAM), Security Command Center, Confidential Computing, and Key Management Service. It also ensures compliance with industry standards and certifications.
• Discounts
  If you use GCP’s per-minute billing offer for computing in conjunction with the Sustained Use Discount, it can be more cost-effective than other providers’ services. It will also be the cheapest of the three when using general-purpose instances and when it comes to monthly charges for a Linux server.
• Focus on Open Source
  As a cloud services provider, GCP takes extra steps to ensure the platform’s compatibility with open-source tools and solutions. This gives software developers more freedom in choosing their development kit and lets them experiment and play with technology freely, relying on Google’s platform.

Cons of GCP

• Price
  Although the cost of using GCP is mentioned as a benefit it can also turn out to be costly. It has the highest prices for compute-optimized, memory-optimized, and accelerated computing instances among the Big Three. However, the discount rate for a year and longer commitment will provide a discount at the highest rate as well. So count well before you choose.
• Coverage and Service Range
  Compared to its two rivals, GCP has the least developed global infrastructure and the shortest service range, even though it has an advantage in some service domains, such as Big Data or Machine Learning. However, now GCP is rapidly gaining traction, bringing it much closer to AWS and Azure with time.

Among the top global companies that prefer Google Cloud Platform as their cloud infrastructure vendor are the following:

• Paypal
• Home Depot
• Twitter
• UPS
• Cardinal Health

To compare GCP, AWS, and Azure, we took into account the benefits and drawbacks each of them has, whether different or similar.

AWS is Best For

• Web application development with such services as Amazon EC2 instances, Amazon S3 for storage, AWS Elastic Load Balancing solution, and AWS CloudFront as a leading service for content delivery.
• Mobile application development using AWS Mobile Hub, AWS AppSync, Amazon Cognito, as well as AWS Lambda and AWS Amplify that are great for mobile backend development.
• Data storage solutions with Amazon S3 service for object storage, Amazon EBS for block storage, and Amazon Glacier for long-term archival. It also offers solutions for different database types with Amazon RDS, DynamoDB, and Amazon Redshift.
• Big Data and BI solutions using Amazon EMR for big data processing, Amazon Athena for ad-hoc query analysis, Amazon Kinesis for real-time streaming data processing, and Amazon QuickSight for business intelligence and analytics.
• IoT and Connected Devices development with AWS IoT Core and AWS IoT Analytics for collection, storage, and analysis of data from IoT devices.

Read our AWS IoT + Cognito: IoT Devices and User Management Solution blog article to learn more about Waverley’s IoT development expertise with the AWS toolset.

Azure is Best For

• Enterprise Application Development with broad tooling for building, deploying, and scaling, including such tool as Azure Logic Apps designed to create workflows for smooth application integration.
• Hybrid Cloud Solutions using Azure Arc to easily manage your resources across on-premises, multi-cloud, and edge environments.
• AI and ML Solutions with Azure Machine Learning for building and deploying ML models, Azure Cognitive Services for pre-built AI capabilities, and Azure Bot Services for building intelligent bots. Don’t forget about the opportunities Azure provides for generative AI solutions due to integration with OpenAI – read our guide on how to integrate ChatGPT into your business.
• Data Warehousing Solutions with the Azure Synapse Analytics service.
• Windows Server and .NET Applications working best with the Azure infrastructure and its Azure Virtual Machines, Azure DevOps, and Visual Studio Team Services as their preferred choice.

Understanding Your Business Needs

To better understand your business needs in cloud resources, try to put down as much information about your project as possible. These questions might be helpful:

• What are my short-term and long-term objectives for using the cloud?
• What resources exactly do I need and how much (e.g. storage, database, compute capacity)?
• What is my users’ geography?
• What are my load, scalability, and performance requirements?
• Am I looking for low-code or pro-code solutions?
• What cloud services will I need for my application architecture?
• Do I need any integrations?
• Does my application fall under certain compliance regulations?
• What can be my security concerns?
• What are my budget limits?
• Who should be responsible for managing and supporting my infrastructure and resources?
• How can I measure my cloud’s infrastructure efficiency?

Finding Your Match

Having a clear picture of your needs and capabilities, you now can get down to researching what cloud service providers have to offer. To choose the cloud service provider that will be right for your business, we recommend paying attention to several key factors, namely:

• The provider’s credentials and quality standards.
• Cloud security options you can make use of
• Industry compliance guarantees for your product
• Solution manageability
• Architecture and integration needs
• Service levels you need
• Support provided

1. Credentials and Standards
   High service quality should be a major concern if you want to develop a reliable software application and avoid wasting your resources. Thus, adherence to industry best practices is a key factor that can determine the choice of the cloud service provider. Taking standards into consideration first should help narrow down the pool of prospective suppliers, while credentials and reviews will add more credibility and certainty.
2. Cloud Security
   If your application will be handling any sensitive information, data security measures must be your top priority. Carefully study each provider’s physical and informational security measures they take, what backup options they provide, and how they mitigate breaches and unforeseen events. Find out the service range the providers offer to meet their clients’ security needs.
3. Cloud compliance
   For digital solutions for highly regulated domains, choose a cloud platform that can meet the compliance standards specific to your industry and business. Find out which cloud provider (s) can ensure compliance within your industry. Once you’ve put your applications and data on cloud infrastructure, understand what it takes to stay compliant. Make sure you understand where your responsibilities lie and what compliance issues your vendor can help you with.
4. Architecture
   Depending on whether you have an existing system or not, draw your application’s architecture design taking into account integration with all your workflows, current and future. For example, if you’ve already invested in the Microsoft ecosystem, opting for Azure may make sense. Additionally, consider your cloud storage architecture. Microsoft, Amazon, and Google all offer multiple types of storage meeting different needs, but the types of archival storage are different. If it matters, make sure you understand the subtle differences between them.
5. Manageability
   Define the level of expertise needed to manage your cloud infrastructure and research what cloud service providers can offer to meet your capabilities. If it turns out that you’ll need to hire a certified cloud expert, consider service options that include infrastructure and resource management on the provider’s part. However, be ready to pay more and have to do with less flexibility and customization opportunities.
6. Service levels
   Service levels are important if your organization has stringent requirements for availability, response time, capacity, and support. A cloud service level agreement will be your main guide (cloud SLA) when choosing a provider. It’s essential to establish a clear, legally binding contractual relationship between the cloud customer and the cloud provider. Pay particular attention to legal requirements regarding the security of data hosted on cloud services, especially regarding compliance provisions.
7. Support
   Another critical factor to consider is support. If you need help, will you get it quickly and easily? Some cloud providers only offer support through a chat service or call center, which may not be acceptable for your needs. Others may offer dedicated resources, but they may have limited time and access. Make sure you inquire about the level and type of support you can access.