Cloud computing is one of the biggest buzzwords of the 21st Century. Cloud computing has gradually become a key driving force for almost every kind of business today.
Modern technologies like Big Data, Artificial Intelligence, Internet of Things, and even the Web and Mobile application design and hosting need very heavy computing power, and here is where Cloud computing scores big.
Cloud computing services offers an alternative to any organization to building its in-house infrastructure with manageable cost, with a capability to scale computing power on a plug and play basis.
Cloud allows saving a huge cost on investment and maintains the costly infrastructure and their periodic up-gradation; hence it has become an extremely exciting and popular solution.
Cloud Computing has been evolving up to great extent in the last decade, it no longer a question if one wants to opt for Cloud computing or not, the question now is which Cloud platform one should go for.
Choosing a top cloud services provider is not an easy task, in this article, we will be providing an honest comparison between AWS vs Azure vs Google Cloud. We will try to highlight and elaborate on the parameters of comparison among AWS, Azure, and GCP, which may help you to choose the best cloud platform for your organization.
We know the numbers talk for themselves, however it is important to know about each Cloud platform in little detail.
Amazon Web Services is a subsidiary of amazon.com. It is unarguably the most popular and oldest Cloud service vendor in the market.
AWS is a secure cloud service that offers compute service, database, storage, data management, hybrid cloud, migration, AI, Big data management, and several other services to support businesses grow and scale per their requirements.
It provides an ‘annual subscription’ pricing model, apart from that AWS offers a ‘free-tier’ option for the organizations or individuals to get hands-on experience at an extremely nominal charge.
AWS was the first cloud vendor which introduced the Pay-as-you-go model, which helps Organizations to save huge cost on infrastructure and resources. AWS has more than 100 services in its portfolio which provides benefits like cost-effectiveness, agility, scalability, flexibility, and security.
Azure was launched in 2010 for providing a competent cloud computing platform for businesses. This platform is developed by Microsoft and it offers a plethora of cloud services including Compute, Database, AI/ML, Storage, Analytics, and Networking.
Azure enabled through Data Centers managed by Microsoft, and it provides Windows Server, Office, SQL Server, Sharepoint development, Dynamics Active Directory, .Net services. It gives a sense of reliability to those who are already using Microsoft Service and applications.
It also supports the development, test, deployment, management, and security of applications and services. For web development, it offers support for PHP, ASP.Net, and Node.JS. Azure development services also helps developers to deploy code on Microsoft’s servers.
Google is comparatively a new entrant; it offers all major Platform services along with Machine Learning and Internet of Things.
It also provides tools for cloud management, security, and development. The Google Cloud Storage supports both SQL (Cloud SQL) and NoSQL (Cloud Datastore) database storage.
GCP offers a unique ecosystem to end users where Google Compute Engine (IaaS) provides users with virtual machine instances for workload hosting. GCP has a strong offering in containers, it was Google which developed the Kubernetes standard that AWS and Azure are offering now.
Our comparison guide is a thorough take on all the three cloud service providers based on the following parameters:
It comes under IaaS (Infrastructure as a Service) which is a collection of key resources helps an organization to carry out its computational abilities. This ability is provided by the high-performance CPU’s connected in form of a ‘cluster’.
| Service | AWS | Azure | GCP |
|---|---|---|---|
| Primary Compute Service | Elastic Compute Cloud (EC2) | Virtual Machine | Compute Engine |
| PaaS | Elastic Beanstalk | Cloud services | Google App Engine |
| Virtual Private Cloud | Lightsail | Virtual Machine Image | VPC |
| Container Deployment | Fargate service, It supports Docker and Kubernetes | Azure Container Service | Kubernetes Engine |
| Running Backend & system integration | Lambda | Event Grid & Web Jobs | Cloud Beta Functions |
| Container Register | EC2 registry | Container registry | Container registry |
| Free Tier Service | Free EC2 instance for 750 hours per month for up to twelve months. | Free Windows or Linux B1S virtual machines for 1 Year | One F1-micro instance per month Free for up to 12 months |
Here it is visible that AWS holds a distinction with a wide variety of services and tools available for end-users.
This service offers Data Storage, scalability, data availability, security, and performance. This service is responsible for storing and protecting vital data for any organization, their websites and applications.
It also offers additional services like backup and restores, archive, enterprise applications, IoT devices, and big data analytics.
| Storage service | AWS | Azure | GCP |
|---|---|---|---|
| Storage | SSS, EBS and EFS | Blob Storage, Queue Storage Data and Lake Storage | Unified Cloud Storage |
| Object Storage | S3 | Blobs and files | Cloud storage block |
| Block storage | EBS | Page Blobs | Persistent disks |
| Hybrid storage | Storage gateway | StorSimple | Egnyte Sync |
| Bulk data transfers | Snowball edge, Import/Export disk & Snow Mobile | Data Box & Import/Export | Storage transfer service |
| Back-up solutions | Glacier | Backup | Cold line |
| Disaster recovery | Disaster recovery | Site recovery | GCP DRaaS |
This section observes a stiff competition between these 3 Cloud vendors; however, it depends on the requirements of the Organization. However, AWS again wins the race with the wide variety of tools and services.
It’s a managed service, which is also known as DBaaS (Database as a Service) that offers tools to set up, manage, control, operate, and scale a relational Database management solutions.
| Database Services | AWS | Azure | GCP |
|---|---|---|---|
| Database Offered | Aurora, RDS, DynamoDB, ElastiCache, Redshift, Neptune | SQL database, Database for MySQL, Database for PostgreSQL, Data warehouse, Server Stretch database, Cosmos DB, Table storage, Redis cache, Data Factory | Cloud SQL, Cloud Spanner, Cloud Bigtable and Cloud Datastore |
| Caching | ElastiCache | RedisCache | CloudCDN |
| Indexed NoSQL | DynamoDB | Cosmos DB | Datastore, Big table |
| Database migration | Database migration services | Database migration services | – |
Here AWS and Azure are fighting neck to neck as both offer support for a wide range of Databases, whereas Google cloud remains behind with a lack of support for all Databases and services.
Networking service allows an organization to setup a Network from scratch or migrate an existing network to the Cloud. It is a NaaS (Network as a Service) which caters the requirements of Network resources connectivity of an enterprise.
It provides a centralized command to management, control the network devices installed at different geographical and physical locations using the internet.
| Networking service | AWS | Azure | GCP |
|---|---|---|---|
| Virtual Network | Amazon VPC | Virtual Networks | Virtual Private cloud |
| Elastic load balancer | Elastic load balancer | Load balancer | Cloud load balancing |
| DNS | Amazon Route 53 | Azure DNS | Google Cloud DNS |
| Peering | Direct Connect | ExpressRoutex | Google cloud interconnect |
As far as Networking service is concerned, it seems all Vendors have evolved and have put together all the services for the Organizations with easy configuration methods.
This is one area where all three platforms are putting their best efforts to integrate AI/ML and IoT technology and tools.
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.
| Advanced Tools | AWS | Azure | GCP |
|---|---|---|---|
| AI/ML | SageMaker, Comprehend, Lex, Polly, Recognition, Machine Learning, Translate, Transcribe, Deeplens, Deep Learning AMIs, Apache MXNet on AWS, TensorFlow on AWS | Machine Learning, Azure Bot Service, Cognitive Services | Cloud Machine Learning, Dialogflow Enterprise Edition, Cloud Natural Language, Cloud Speech API, Cloud Translation API, Cloud Video Intelligence, Cloud Job Discovery |
| IoT | IoT Core, FreeRTOS, Greengrass, IoT 1-Click, IoTAnalytics, IoT Button, IoT Device Defender, IoT Device Management | IoT Hub, IoT Edge, Stream Analytics, Time Series Insights | Cloud IoT Core |
| Serverless Tools | Lambda | Functions | Cloud Functions |
As we said, all 3 Vendors are investing heavily for AI/ML and IoT tools, but if we see the current proposition, then again AWS wins this with little margin, as it offers a wide range of tools that help organizations to integrate the emerging technologies into their projects.
An Availability Zone is a discrete Datacenter within the geographical region, from where a cloud service provider can offer cloud services to its customers.
These Datacenters have huge computing resources along with redundant power and network connectivity. Availability zones offers required resources to Organizations, so that they can operate their applications and databases from a single data center.
| Availability Zones and Regions | AWS | Azure | GCP |
|---|---|---|---|
| Availability | 77 Availability Zones, 9 more to be added soon. Available in 24 geographic regions, 3 more regions to be added soon. | Azure caters to 54 regions worldwide and is available in 140 countries. | It is available in 20 regions around the world with 3 more to be added soon. |
Here AWS is again a clear winner with wider Geographical coverage and more locations in pipeline.
All 3 Players provide a wide range of pricing models for customers. AWS offers the Pay-as-you-go mechanism, which provides huge flexibility to the organizations to pay for only used resources and services without paying any long-term licensing.
However, the cost calculation is a bit difficult in AWS, and sometimes it is difficult to make accurate estimates. Recently AWS has switched from by-the-hour to by-the-second pricing model, which makes it a bit more competitive.
Azure development on the other hand offers much affordable pricing as they charge on a minute basis. However, due to Microsoft’s complex software licensing options and the use of situation-based discounts, its pricing structure can confuse one easily.
GCP also charges on a minute basis, also neither there is an up-front cost nor there any termination fees. GCP is known for making Pricing as a primary differentiator with other Cloud vendors. It offers customer-friendly and flexible prices and that is the major reason behind its ever-increasing clientele.
| Pricing | AWS | Azure | GCP |
|---|---|---|---|
| Smallest Instance | 2 virtual CPUs and 8 GB of RAM will cost nearly US$69 per month | Instance with 2 vCPUs and 8 GB of RAM, in Azure, costing US$70/month | 2 virtual CPUs and 8 GB of RAM at a 25 percent cheaper rate costing US$52/month |
| Largest Instance | 3.84 TB of RAM and 128 vCPUs will cost around US$3.97/hour | 3.89 TB of RAM and 128 vCPUs. It costs around US$6.79/hour | 3.75 TB of RAM and 160 vCPUs. It will cost close to US$5.32/hour |
Here it is quite evident that Google Cloud Platform wins this race hands down, with its attractive and flexible pricing model.
Google also offers aggressive discounts to its customer. AWS and Azure should work more on mitigating the pricing issues and calculation complexities.
It is undoubtedly the most important metric to measure the quality of a Service provider. Uptime is an SLA (Service Level Agreement) which is a measure of the time when a service is to the end user.
It is said that Uptime is directly proportional to the customer satisfaction and it indeed an important parameter that should be kept in mind while choosing a Cloud service provider.
| Uptime SLA | AWS | Azure | GCP |
|---|---|---|---|
| Uptime SLA | Amazon EC2- 99.5% annual uptime
Amazon S3 — A monthly uptime of at least 99.9% for a billing cycle |
99.9% uptime | 99.95% monthly uptime |
Here we can see that Azure has a clear advantage as far as uptime SLA is concerned.
If we talk about the market share, then AWS is the clear winner hands down. As per Canalys report (Feb-2020), AWS is the market leader with whooping 32.4% share of the market, Azure stands at 17.6% whereas Google Cloud Platform is a distant third with 6% market share.
AWS avails an unusual advantage of a seven-year head start, before other competitors ventured out in this field.
However, it is quite evident that Azure and GCP are catching up fast, which reflects in their respective annual growth rates. But currently the AWS hold a huge lead in this area.
As we can see, AWS scores more points in this cloud battle and wins this race handsomely. It offers wider number of features, services and tools. However, that doesn’t necessarily mean it is best for your organization.
If an organization runs most of its operations on Microsoft products, then Azure development services could be the best bet, since it’s easy to integrate Microsoft tools with Azure cloud.
On the other hand, GCP offers the best pricing model for the infrastructure, on which Google Search engine and YouTube run. If any business needs acceptable reach and more innovation might prefer Google Cloud Platform.
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