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Amazon Web Services (AWS), Microsoft Azure, and Google Cloud are leading cloud service providers, each with a primary strength.

  • AWS offers a massive ecosystem with a vast selection of solutions.
  • Azure seamlessly integrates with Microsoft products and focuses on enterprise solutions.
  • Google Cloud stands out for its data analytics and machine learning (ML) capabilities.

Understanding the unique strengths of each will help you choose the correct cloud platform for you.

AWS vs. Azure vs. Google Cloud Comparison

Here’s a comparison of AWS, Azure, and Google Cloud based on the services they offer across compute, storage, databases, ML, and security:

AWSMicrosoft AzureGoogle Cloud
ComputeEC2, Lambda, Lightsail, Batch, APP Runner, ECSVirtual Machines, Azure Functions, App Services, Kubernetes Service, Container Apps, BatchCompute Engine, Cloud Functions, App Engine, VMware Engine, Cloud Run, Recommender
StorageS3, EBS, EFS, Backup, Glacier, Elastic Data RecoveryData Lake Storage, Disk Storage, File Storage, Container Storage, Blob Storage, Azure NetApp FilesCloud Storage, Persistent Disk, Filestore, Storage Transfer Service, Transfer Appliance, Nearline
DatabasesRDS, DynamoDB, DocumentDB, Aurora, RDS, RedshiftAzure SQL, Cosmos DB, Cache for Redis, Database Migration Service, Azure Database for MySQL, Azure Database for PostgreSQLCloud SQL, Firestore, Bigtable, Memorystore, Spanner, Datastream, AlloyDB
Machine learning (ML)SageMaker, Augmented AI, Bedrock, CodeGuru, Comprehend, ForecastAzure ML, Cognitive Search, OpenAI Service, AI Speech, AI Vision, AI Content SafetyVertex AI Platform, AutoML, Dialogflow, Natural Language, Vision AI, Video AI
Security & identityIAM, Shield, Cognito, Detective, Inspector, GuardDutyApplication Gateway, Microsoft Sentinel, Key Vault, Azure Firewall, Web Application Firewall, Azure DDoS ProtectionIAM, Cloud IDS, Cloud Armor, Identity Platform, Cloud Key Management, Cloud Data Loss Prevention, Identity-Aware Proxy
Pay-as-you-go pricing
Visit AWSVisit Microsoft AzureVisit Google Cloud

Should the criteria covered above not do enough to help you make an informed choice, check out their websites for more product and service criteria offered.

What is Amazon Web Services (AWS)?

AWS is a widely adopted cloud platform that provides fully featured on-demand cloud services to individuals, start-ups, enterprises, and government agencies with cloud services like computing power, storage options, and networking capabilities.

AWS key differentiators

Some of the more distinct features of AWS include compute cloud, distributed ledgers, serverless services, the Internet of Things (IoT), and a vast and mature network.

  • Elastic Compute Cloud (EC2): EC2 is a broad compute platform that allows users to run virtual machines (VMs) and scale computing capacity while supporting Intel, AMD, and Arm processors.
  • Blockchain on AWS: AWS gives users the tools to create distinct blockchain networks alongside a broad ecosystem of 70+ validated blockchain solutions from partners.
  • Serverless computing: Automatic scaling and built-in high availability are part of AWS’s serverless technologies for running code, integrating applications, and managing data.
  • IoT services: AWS IoT Core and other IoT services connect billions of devices and collect, store, and analyze IoT data for industrial, consumer, automotive, and commercial workloads.
  • Strong ecosystem: AWS has a vast ecosystem of third-party integrations and a large community, providing extensive support and resources.

AWS pricing

With over 190 cloud products, AWS offers pay-as-you-go pricing that varies based on the services used, but specific pricing information beyond AWS’s pricing calculator isn’t provided.

AWS pros and cons

AWS is a mature platform with a wide array of services, making it suitable for various use cases, industries, and organizations. The platform also benefits from a vast global reach, ensuring its services are of low latency and comply with regional data laws. AWS offers a free tier to provide hands-on experience with the platform.

However, the sheer number of services can make the platform overwhelming and may require specialized skills to navigate. The pricing model, while flexible, can be confusing and lead to unexpected costs. Plus, AWS’s focus on a broad service offering can sometimes result in less attention to specialized services.

Should you prefer a more specialized cloud platform, consider Google Cloud Platform as it’s quite thorough despite fewer unique offerings.

aws vs azure vs google cloud

What is Microsoft Azure?

Microsoft Azure is Microsoft’s cloud computing service that empowers businesses to develop, test, deploy, and manage their applications and services. Azure provides a variety of services, including those for computing, data and analytics, hybrid cloud, security and governance, and cloud migration.

Azure key differentiators

Azure’s offering includes on-premises, multi-cloud and edge solutions, cloud migration tools and services, vast artificial intelligence (AI) solutions, blockchain services, and cloud security services.

  • Strong focus on hybrid cloud: Azure has a robust set of tools for hybrid cloud environments to simplify the integration of on-premises data centers with the cloud.
  • Migration and modernization: Users have tools, resources, and guidance at their disposal to ease and accelerate their cloud migration and modernization.
  • Azure AI: Azure offers a portfolio of AI services for data scientists and developers, cutting across vision, language, speech, and decision-making models.
  • Web3 services: With Azure, organizations can implement blockchain as a service to build, deploy, and scale decentralized applications.
  • Security and governance: Services such as Azure governance, backup and disaster recovery, network security, and confidential computing ensure all-around cloud security.

Azure pricing

Like AWS, Azure offers a large number of distinct products, and it too uses a pay-as-you-go model, with a pricing calculator to help users estimate their costs.

Azure pros and cons

One of Azure’s greatest strengths is that it seamlessly integrates with Microsoft products, making it a worthy choice for businesses already invested in the Microsoft ecosystem. Its strong focus on hybrid cloud solutions makes data management more flexible. Additionally, the platform also offers robust AI and blockchain tools, catering to businesses with data-intensive needs and those centered around decentralized applications.

But Azure has a steeper learning curve compared to other platforms, and its focus on enterprise solutions can make it less suitable for small businesses. Even though it has a clearly defined pricing calculator, the cost structure can be complex, which may lead to unexpected expenses. However, to make sure you get accurate pricing information, you can always reach out to Azure sales.

aws vs azure vs google cloud

What is Google Cloud Platform (GCP)?

Google Cloud Platform (GCP) is a collection of Google’s cloud computing services that deliver products across AI and ML, compute, storage, databases, data analytics, developer tools, and networking.

GCP key differentiators

With GCP, some of the greatest capabilities its users receive include hybrid and multi-cloud deployments, big data analytics, AI-powered code and applications, customizable VMs, and scalable and serverless databases.

  • Open source and multi-cloud: Google Cloud is designed with an open architecture that supports multi-cloud and hybrid cloud deployments.
  • Data analytics strength: GCP excels in big data analytics and offers dozens of data analytics tools, like BigQuery for high-speed SQL queries and Looker for business intelligence.
  • AI and ML emphasis: Customers can build generative AI applications and conversational AI products, generate AI-powered code, and more with Google’s strong focus on AI and ML.
  • Compute Engine: Google Cloud’s Compute Engine enables customers to build and run customizable VMs, automatically deploy containers, and migrate applications.
  • Fully managed databases: GCP uses fully managed PostgreSQL, MySQL, and SQL Server databases to lower maintenance costs for its clients and help them develop rich applications.

GCP pricing

Pricing is flexible, following a pay-as-you-go model. Google encourages prospective users to contact them for a quote. One advantage they offer over competitors is that new customers receive $300 in free credits to run, test, and deploy their workloads.

GCP pros and cons

GCP plays a massive role in the development of many open-source technologies. And its open architecture makes it flexible for multi-cloud and hybrid cloud deployments. The platform also has a strong focus on AI and ML, offering advanced capabilities in these areas. Additionally, GCP also shines when it comes to conducting cutting-edge research.

Google Cloud, however, has a smaller community compared to AWS, which may result in fewer third-party integrations and community support. Plus, the platform’s focus on data analytics can overshadow its other offerings. If community support and a greater number of integrations are a must-have for you, AWS is worth a look instead.

aws vs azure vs google cloud

Best for pricing: Google Cloud Platform

For pricing options, GCP emerges as the winner of the three cloud solutions. It delivers sustained use discounts that lead to lower costs for continuous use of certain services and custom and preemptible VMs.

Add that to the innovative pricing models associated with Google products and the generous free tiers and credits for new customers and smaller businesses, and it’s clear that GCP is as flexibly priced as anything in this category. For instance, as mentioned previously, Google gives $300 in credits to new customers.

That being said, AWS and Azure also offer attractive pricing features, and in practice the best pricing features may vary depending on a client’s use case. To deal with these variations and nuances around pricing, each provider offers a pricing calculator to help prospective users estimate how much a product will cost them.

Best for core features: AWS

AWS’s features catalog is expansive and diverse. It’s not only the sheer number of the services it offers, but the quality of these services that makes AWS stand out. AWS has a solution in almost every cloud niche, from foundational services like EC2 for computing and S3 for storage to more specialized offerings in analytics, IoT, and ML.

To complement these services is a global network that features many data centers spread across various regions and availability zones, ensuring that AWS offers high availability, fault tolerance, and scalability for any application. The adoption of AWS by industry giants across various sectors underscores its capability to serve a broad spectrum of cloud computing needs.

Best for ease of implementation: Azure

This is a close one and can vary based on the use case, but Azure edges out the other two providers simply because of the ubiquity of Microsoft products. Azure offers seamless integration with the Microsoft ecosystem, which makes transitioning to cloud or hybrid environments that much easier. Azure also has a strong focus on hybrid cloud solutions and is particularly strong at packaging enterprise focused services.

Still, AWS and Google Cloud may be considered easier to implement based on scenarios where their unique strengths align more closely with the project’s requirements. Highly scalable global applications may find AWS’s extensive array of services and global infrastructure easier to implement, while other teams may find Google Cloud’s strengths in data analytics and ML ideal for projects focused on these areas.

Best for AI and ML applications: GCP

Google Cloud stands out when it comes to AI and ML applications, thanks to its focused approach to the ML process. In particular, Google’s Vertex AI platform is easy to use, clean, and takes a containerized approach, which sets ideal conditions for the development and deployment of ML models.

GCP’s strength in AI and ML is further bolstered by its extensive internal research and expertise, much of which powers Google’s own products and services. Vertex AI integrates with Google’s array of AI and ML tools, including TensorFlow and a range of AI APIs for vision, language, conversation, and structured data. It’s a thorough solution for developers and data scientists looking to leverage the latest in AI technology.

The platform’s emphasis on open-source technologies and its central role in developing Kubernetes for orchestration show just how invested Google is in AI applications.

Best for Hybrid Cloud Capabilities: Azure

Azure’s hybrid cloud capabilities offer seamless integration with existing Microsoft environments such as Windows Server, Active Directory, and SQL Server, and provide a cohesive experience, especially for businesses deeply entrenched in Microsoft’s ecosystem.

Azure Stack, in particular, extends Azure’s cloud services to on-premises environments, allowing for a truly consistent hybrid cloud experience. This enables businesses to develop and deploy applications in the same way, regardless of whether they’re running in the cloud or on-premises. This makes it uniquely flexible and offers granular control over where workloads reside.

Bottom line: The best cloud provider for MSPs

To choose the best cloud provider, consider which platform provides the best balance between your desired features and budget to ensure that your teams aren’t overrun as your cloud needs grow. And be sure to factor in all your expected costs when you use each platform’s price calculator.

If you’re considering more specific cloud services, such as migration services, read our guide to the top cloud migration services providers for more insights.