AWS is the market leader in the cloud service provider market and continues to grow exponentially. They were the first provider in the market since 2006 and have great capabilities and extensive services. Microsoft Azure came to the cloud market in 2010 extending and building its enterprise customers to the cloud. Google cloud has been in the market since 2008 and created its own mark with commitment to open source, multi cloud and hybrid cloud. As a cloud service provider, they have great technical expertise in open computing and have industry-leading tools in Deep learning, AI, Machine Learning, and Data Analytics.
- Cloud Provider Overview
- Storage Comparison
- Compute Comparison
- Tools Comparison
- Pricing Comparison
- Which Cloud Provider is Best For My Business
Cloud Provider Overview
All three cloud service providers offer the standard IaaS and PaaS benefits. So, to choose a cloud provider that fits your needs without stretching your budget we need to explore the finer differences. The following list gives some particularly important considerations (which is applicable to all) while choosing a cloud provider.
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- Evaluate stability. That means availability of regular releases, continuous performance, dispersed platforms, and load balancing.
- Find a reliable provider. This goes beyond name recognition to include emphasis on security and feedback from real customers.
- Consider economies of scale. What is the ratio between the cost of running an in-house server versus the available resources of an enterprise cloud?
- Look for standardized service. Does the company offer cost-effective bundles of apps and the resources you need? Bundled services can save 40 percent over purchasing a la carte IaaS, SaaS, and other digital products.
- Evaluate flexibility. The last thing you want is to be locked into a contract with a provider that inhibits agility and growth.
AWS Service Overview
Amazon Webservices is a robust cloud computing platform for enterprises. The vast global framework and dispersed of Amazon Web Services is what the entire platform is built upon. As of July 2021, AWS Cloud spans 25 geographic regions around the world with total of 81 Availability Zones within, with announced plans for 21 more Availability Zones and 7 more AWS Regions in Australia, India, Indonesia, Israel, Spain, Switzerland, and United Arab Emirates (UAE) and 218+ Edge Locations and 12 Regional Edge Caches.
The regions cover a geographic area such as a state or country, and the AZ’s are data centers within regions. The availability zones are located as far as possible from each other within their region to ensure that there are no lapses in service if one AZ goes down due to a natural or other type of widespread disaster. Edge zones are caches that act in a similar manner to content delivery networks (CDN’s) by caching web content nearer to the location of the user for faster delivery and response times.
This type of infrastructure allows data delivery to deploy faster and on a global scale without affecting the availability of service or performance. AWS supports all operating systems and generally ranks as the top IaaS platform for availability, reliable performance, and the number of applications. So far, there are 18,000 distinct services and counting. They include:
- Developer, engagement, and management tools
- Machine learning and predictive analytics
- Databases and storage solutions
- Business productivity tools
- App integration
Azure Service Overview
Azure is known as a solid, integrated platform for companies that already rely on Windows-based standardization, Microsoft Azure has overcome some obstacles to compete head-to-head with AWS. One surprising feature is its Linux-friendliness as it relates to virtual guest operating systems and compatibility with Linux container platforms.
The strength of Azure was always as a provider of Infrastructure-as-a-service (IaaS), Azure also comes with built-in and ready to run server apps that support a range of languages, including .NET, Java, PHP, Node.js, and Python. The physical component is comprised of 200+ physical datacenters, arranged into regions, and linked by one of the largest interconnected. It is also one of the easiest enterprise clouds when it comes to configuring and operation. It has specialized services which include.
- Big data and predictive analytics.
- Game and app development
- Scalable data warehousing
- Blockchain technology
- IoT integration
Google Cloud Service Overview
As far as IaaS providers go, Google Cloud Platform is the relative newcomer. It supports several generations of Linux in addition to Windows server versions up to 2016. As of 2021 July, it has expanded to 25 regions, 76 zones, 144 network edge locations and 200 plus countries.
It has all the functionality operable through a new console that was designed with ease of use in mind, and it is simple to set up and configure. Services include:
- Data management and storage
- App development
- SMB business analytics and AI
- Productivity and workload management tools
One of the greatest advantages of cloud computing is the expansive storage capabilities. As with most features, each platform is strong in different ways. AWS has a wide range of storage options. Backup solution from AWS is Glacier and Glacier deep archive but it has no recovery solution.
Azure has more specialized solutions like their Data Lake that is specifically designed for large, data-rich applications. Azure is the only platform providing several backup solutions, including archival storage. Google offers fewer storage options, but they are more unified and targeted. All three platforms include several types of databases, with Azure offering the widest variety and sizes.
AWS Storage Services
This is one area where AWS does delve into offering a hybrid platform through its Storage Gateway. Gateway offers a secondary archival storage option in conjunction with Amazon’s sole backup feature, Glacier. Users can opt for simple object storage with S3 or block storage for large containers with their elastic block feature. In addition, the elastic file storage expands your capability as you create files, which is ideal for large corporations that generate a lot of data. Amazon Web Services also provides several SQL-supported databases, an ElastiCache feature to provide additional memory, and a data migration service.
Azure Storage Services
Azure offers a dedicated storage option called Blob Storage. This is reserved for unstructured, REST-based object warehousing. Like AWS, they also have solutions for large-scale data storage and high-volume, critical workloads with their Queue Storage and Data Lake Store. This platform also provides users with the largest array of databases, which support three different SQL-based formats, and their Data Warehouse gives you room to grow.
The support that Azure provides for SQL is not limited to storage. Their Server Stretch database is a hybrid that offers on- and off-premises storage for companies that use Microsoft SQL Server for their enterprise but might utilize other protocols on the cloud. This is the only company of the three that has a backup recovery system, which is in addition to their archival and standard system backups.
Google Storage Services
Google Cloud Platform offers basic storage and database support, but little else. Their storage solutions are like what GCP provides customers in the compute department, and they provide both SQL and NoSQL database support. They do have a transfer appliance that is like AWS Snowball, and several online transfer services are available.
|Service category||Service type||AWS offering||Azure offering||Google Cloud product|
|Storage||Block storage||Amazon Elastic Block Store (EBS)||Azure Disk Storage||Persistent Disk|
|Storage||File storage||Amazon Elastic File System (EFS)||Azure Disk Storage, Azure Files||Filestore|
|Storage||Infrequently accessed object storage||Amazon S3 Glacier||Azure Archive Storage||Cloud Storage Archive|
|Storage||Object storage||AWS Simple Storage Service (S3)||Azure Blob Storage||Cloud Storage|
|Backup Services||Archival||Glacier and Glacier deep archive||Archival storage||Nearline and Coldline|
|Backup Services||Recovery||Recovery backups|
|Backup Services||Site Recovery||Site recovery|
|Database||Document data storage||Amazon DocumentDB,
AWS DynamoDB, AWS AppSync
|Azure Cosmos DB||Firestore|
|Database||In-memory data store||Amazon ElastiCache||Azure Cache||Memorystore|
|Database||NoSQL: Indexed||Amazon DynamoDB||Azure Cosmos DB||Datastore|
|Database||NoSQL: Key-value||Amazon DynamoDB||Azure Cosmos DB||Cloud Bigtable|
|Database||RDBMS||Amazon Aurora||Azure SQL Database||Cloud Spanner|
|Database||RDBMS||Amazon Relational Database Service (RDS),
|Azure Database for MySQL and
Azure Database for PostgreSQL
|Database||Relational||Amazon RDS for Oracle||Azure Oracle Database Enterprise Edition||Bare Metal Solution|
The fact that AWS had a seven-year head start makes it a better-known and more seasoned enterprise cloud platform. But does that make it the best? Each of the “Big Three” business cloud service providers have benefits and drawbacks that may differ according to your own requirements and circumstances.
Amazon has a wider reach and availability of services, and it has dominated the market since its release. Windows has the advantage of built-in compatibility since most companies already depend on Microsoft products for daily business operations.
However, Google Cloud Platform also integrates with its wide range of products and platforms, world-class analytics, and ownership of the world’s two largest search engines, Google and YouTube. It also supports almost any operating system and offers flexibility due to a commitment to open source. Google is also an innovator when it comes to cloud-native business solutions.
There are several components that all three platforms have in common, including a high degree of scalability, per-second billing, speed, security, and agility. Their main computational services are where the differences could be a deal-breaker.
AWS Compute Features
The primary compute service is the Amazon Elastic Compute Cloud. EC2 integrates with most Amazon Web Services, promoting compatibility and a high degree of flexibility, which for example: allows database administrators to optimize for cost. The cloud platform allows you to scale up or down in minutes, and it can deploy thousands of server instances at lightning speed. Using the AWS auto scaling monitor puts machine learning to use by monitoring your apps and scaling to capacity according to your current requirements without padding the price. They also promise 99.99 percent availability as part of their service level agreement (SLA). Amazon Elastic Kubernetes Service (Amazon EKS) gives you the flexibility to start, run, and scale Kubernetes applications in the AWS cloud or on-premises. Amazon EKS helps you provide highly available and secure clusters and automates key tasks such as patching, node provisioning, and update.
Amazon Elastic Container Service (Amazon ECS): This scalable container orchestration supports Docker containers through a series of API calls. With this ability, you can begin or end Docker-enabled apps, query the state of your application, manage website IP address blocking and unblocking, and access security groups, IAM roles, CloudWatch events, CloudTrail logs, and CloudFormation templates. There is also an ECS registry feature and a container service for Kubernetes.
Azure Compute Features
Azure compute features rely on a network of virtual machines to enable a range of computing solutions that include development, testing, datacenter extensions, and app deployment. It is based on an open-source platform that is compatible with Linux, Windows servers, SQL Server, Oracle, and SAP. Azure also offers a hybrid model that combines on-premises and public clouds, and it can be integrated into global load balancing.
Azure Kubernetes Service (AKS) is a container system that allows containerized applications to be deployed and managed faster. It offers a seamless continuous integration/continuous delivery (CI/CD) experience, security, and enterprise governance to unite diverse teams working within a virtual office setting on a single platform.
Google Cloud Compute Features
If you are a fan of Kubernetes containers, then Google Cloud may be the choice for you. This company had a hand in developing the popular platform, and it is their main service model. Google Cloud also supports Docker containers.
Cloud Functions is still in the beta phase, but it shows a lot of promise with various features. You can allow the service to manage resources and deploy apps for you, automatically scale according to traffic or use in real-time, and deploy code from Google Cloud, Firebase, or Assistant. You can also call functions up using HTML from any network or device. Best of all, you only pay when your code is deployed.
|Service category||Service type||AWS offering||Azure offering||Google Cloud Product|
|Compute||Core compute||Amazon Elastic Compute Cloud (EC2) P3||GPU Optimized VMs||Cloud GPUs|
|Compute||Core compute||Amazon Elastic Compute Cloud (EC2)||Azure Virtual Machines||Compute Engine|
|Compute||Core compute||AWS Autoscaling||Azure Autoscale, Azure Virtual Machine Scale Sets||Compute Engine Autoscaler|
|Compute||Core compute||Amazon EC2 Instance Connect||OS Login|
|Compute||Core compute||Amazon Elastic Block Store (EBS)||Azure Managed Disks||Persistent Disk|
|Compute||Dedicated VMs||Amazon EC2 Dedicated Host||Azure Dedicated Host||Sole-tenant nodes|
|Compute||FaaS||AWS Lambda||Azure Functions Serverless Compute||Cloud Functions|
|Compute||PaaS||AWS Elastic Beanstalk||Azure App Service||App Engine|
|Compute||VMware connectivity||VMware Cloud on AWS||Azure VMware Solution||VMware Engine|
One thing all three platforms seem committed to advancing is AI and machine learning technology. Although all are strong when it comes to advanced technology, only AWS offers more than one serverless tool. Below is a comparison of how each platform rates in terms of AI, IoT networking, and serverless platforms.
AWS Key Tools – AWS is leading the push to bring AI and IoT to enterprises through an even dozen ML and eight IoT services. Their three key tools will allow you to utilize SageMaker for staff training and deploying machine learning, and you can use the same tech that powers Alexa through their Lex interface.
The Lambda serverless computing environment will give you the freedom of being completely untethered, and you can deploy all of your apps from their serverless repository. In addition, AWS allows you to integrate a range of IoT enterprise solutions that are designed to outfit you with the office of the future.
Azure Key Tools – Microsoft offers fewer AI-enhanced tools than AWS, but the ones they have developed are designed to perform specific functions within your organization. Their Cognitive Services is a suite of API-supported tools that integrate with on-premises Microsoft software and business apps.
The sole serverless platform, Functions, is an event-driven platform that helps you orchestrate and manage complex workloads. Microsoft’s IoT offerings, like Edge, are geared toward management and business analytics.
GCP Key Tools – The reigning champion of algorithms and SEO has a strong AI/ML game, especially when it comes to developing enterprise solutions. Their cloud-based enterprise features run the gamut from natural language, translation, and speech that is ideal for transitioning into global enterprise coordination to ML app development.
This is possible due to their large open-source library TensorFlow, which has even been adopted by AWS. Although their sole IoT and serverless platforms are still in the beta stage, the future of AI implementation looks promising on GCP.
|Service category||AWS offering||Azure offering||Google Cloud Products|
|Developer tools||AWS SDKs, AWS Toolkit for IntelliJ, Visual Studio Code, AWS CloudShell, CLI||Azure SDKs, Azure Toolkit for IntelliJ, Visual Studio Code, Azure Cloud Shell, CLI||Cloud SDKs, Cloud Code for IntelliJ, VS Code, Cloud Shell|
|Internet of things (IoT)||AWS IoT Core||Azure IoT Hub||Cloud IoT|
|Machine learning (ML)||AWS Cost Optimization, AWS SageMaker, Amazon EC2 P3, Tensorflow on AWS, Comprehend, Personalize, Translate, Transcribe||Azure Advisor, Azure Conversational AI,
AutoML in AzureML Studio, Azure AI Platform,
Azure Machine Learning, Cognitive Services, Data Science VM, Notebooks, Databricks, Text Analytics, Personalizer, Translator, Video Indexer, Computer Vision, Speech to Text.
|Recommender, Diagflow, AI Platform (Unified),
AI Platform Deep Learning VM Image, AI Platform Notebooks, TensorFlow Enterprise, Cloud Natural API, Recommendations AI, AutoML Translation, Video Intelligence API, Cloud Vision, Speech to Text
|Serverless||AWS Simple Storage Service (S3), Cognito, DynamoDB + AppSync, Pinpoint, Amazon Device Messaging(ADM),Amazon Simple Notification Service (SNS),EventBridge, Fargate, Device Farm, Step Functions||Azure Blob Storage, Azure Active Directory (AD), GitHub Pages, Static WebApps, Cosmos DB, Notification Hubs, App Configuration, Event Grid, Kubernetes Service, Azure App Center, Azure Functions||Cloud Storage for Firebase, Firebase Auth, Firebase Hosting, Firebase Realtime Database, A/B Testing, Cloud Messaging, Dynamic Links, In-App Messaging, Remote Config, Google Analytics, Eventarc, Knative, Firebase App Distribution, Crashlytics, Performance Monitoring, Test Lab, Workflows|
Pricing is difficult to parse with each of these companies, but there are some similarities and distinctions. All three offer a free tier of service with limited options, and they all charge on-demand for the resources you use.
AWS Pricing -There is not a whole lot of transparency here, although the platform does provide its customers with a cost calculator. The pricing structure is so complex, we recommend using a third-party management app to help you navigate through your options and contain costs. They do offer 750 hours of EC2 service per month for up to 12 months as part of their free tier.
Azure Pricing – This is another platform where it will benefit you to obtain expert guidance. The pricing options are mainly situational to cater to the unique needs of each customer. Like AWS, Azure offers 750 hours of the Windows or Linux B1S addition of their primary compute platform, Virtual Machines, per year (it’s free to try, which is nice for any business who wants to test the cloud “waters”).
GCP Pricing – Pricing is one area where Google tries to stand apart from the crowd by making its pricing structure a little less opaque and more customer-friendly. They strive to beat the list prices offered by most cloud services providers and give steep discounts and other incentives to win business. Google’s free tier incentive includes one F1-micro instance per month for up to one year. If you are looking for an easy-to-navigate, budget-friendly service that shows promising growth potential, this is the platform for you.
Which Cloud Provider is Best for My Business?
The things that all three platforms have in common are on-demand pricing, a free tier, great support, and an emphasis on security. All are brought to you by reputable companies that exemplify tech innovation. However, there are some important distinctions.
AWS is a good fit if:
- Looking for maximum global reach
- If stable, reliable service from a cloud platform is business-critical for a company with a long track record.
- Flexibility is key and requires a wider range of services.
- Enterprise customer or starting from scratch.
Azure is a good fit if:
- Migrating to the cloud for the first time
- Most of your business apps and platforms are Windows-based.
- Looking for a hybrid solution
- Ideal for startups and developers
- Architecture has built-in business continuity with Availability zones and Azure region pairs.
Google Cloud is a good fit if:
- Looking for a comprehensive container-based model
- Well ahead in digital migration and wants to become leaner and more cost-efficient.
- Website works within a hyperscale networking environment.
- Develop and deploy cloud-based software and applications.
- Looking for a green tech solution
When it comes to market share, AWS is the market leader. This is due to a number of features, its global reach, and length of time on the market. However, that does not necessarily translate to what is better for your company. Our goal with this head-to-head comparison is to help business owners like you make informed decisions. If most of your business operations run on Microsoft products, Azure might work better for you. Businesses that need less reach and more innovation might prefer the Google Cloud Platform.
In the end, the choice is yours. Choose wisely.