The public cloud environment is dominated by Amazon, Microsoft and Google, which offer the most stable, scalable and efficient cloud services. AWS, Azure and GCP, their related cloud services, provide consumers a variety of storage, computing and networking solutions.
Instant provisioning, self-service, autoscaling, identity management, authentication and enforcement are some of the standard features of the three systems.
At current, in terms of versatility and sophistication, all of the three platforms are very efficient. To prove their business superiority, the three platforms are now advancing at a quicker pace.
|AI/ML||1) Sage Maker
6) Machine Learning
9) Deep Lens
10) Deep Learning AMIs
11) Apache MXNet on AWS
12) TensorFlow on AWS
|1) Machine Learning
2) Azure Bot Service
3) Cognitive Services
|1) Cloud Machine Learning Engine
2) Dialogflow Enterprise Edition
5) Cloud Natural Language
6) Cloud Speech API
7) Cloud Translation API
8) Cloud Video Intelligence
9) Cloud Job Discovery (Private Beta)
|Storage Services||1) Simple Storage Service (S3)
2) Elastic Block Storage (EBS)
3) Elastic File System (EFS)
4) Storage Gateway
6) Snowball Edge
|1) Blob Storage
2) Queue Storage
3) File Storage
4) Disk Storage
5) Data Lake Store
|1) Cloud Storage
2) Persistent Disk
3) Transfer Appliance
4) Transfer Service
|Computer Services offered||1) AWS Beanstalk
2) Amazon EC2
3) Amazon EC2 Auto-Scaling
4) Amazon Elastic Container Registry
5) Amazon Elastic Kubernetes Service
6) Amazon Lightsail
7) AWS Serverless Application Repository
8) VMware Cloud for AWS
9) AWS Batch
10) AWS Fargate
11) AWS Lambda
12) AWS Outposts
13) Elastic Load Balancing
|1) Platform-as-a-service (PaaS)
2) Function-as-a-service (FaaS)
3) Service Fabric
4) Azure Batch
5) Cloud Services
6) Container Instances Batch
7) Azure Container Service (AKS)
8) Virtual Machines Compute Engine
9) Virtual Machine Scale Sets
|1) App Engine
2) Docker Container Registry
3) Instant Groups
4) Compute Engine
5) Graphics Processing Unit (GPU)
|Backup Services present||Glacier||1) Archive Storage
3) Site Recovery
|1) Nearline (frequently accessed data)
2) Coldline (infrequently accessed data)
|Serverless computing feature||1) Lambda
2) Serverless Application Repository
|Functions||Google Cloud Functions|
|Various Advantages||1) Dominant market position
2) Extensive, mature offerings
3) Support for large organizations
4) Global reach
5) Flexibility and a wider range of services
|1) Second largest provider
2) Integration with Microsoft tools and software
3) Broad feature set
4) Hybrid cloud
5) Support for open source
6) Ideal for startups and developers
|1) Designed for cloud-native businesses
2) Commitment to open source and portability
3) Flexible contracts
4) DevOps expertise
5) Complete container-based model
6) Most cost-efficient
|Type of Caching||Elastic Cache||Redis Cache||Cloud CDN|
|Database Services offered||1) Aurora
7) Database Migration Service
|1) SQL Database
2) Database for MySQL
3) Database for PostgreSQL
4) Data Warehouse
5) Server Stretch Database
6) Cosmos DB
7) Table Storage
8) Redis Cache
9) Data Factory
|1) Cloud SQL
2) Cloud Bigtable
3) Cloud Spanner
4) Cloud Datastore
|File Storage format||EFS||Azure Files||ZFS and Avere|
|Location||77 areas of availability across 24 geographical regions||Present in more than 60 regions across the world||Present in 24 regions and 73 zones. Is there in 200+ countries and territories|
|Price and different Offers||A free trial of one year along with a discount of up to 75% for a commitment of 1-3 years.||Up to 75% discount for a commitment ranging from one to three years||apart from a sustained use discount of up to 30%, GCP Credit of $300 for 12 months|
|Security provided||AWS Security Hub||Azure Security Center||Cloud Security Command Center|
|Networking Type||Virtual Network (VNET)||Virtual Private Cloud (VPC)||Cloud Virtual Network|
|Documentation||Best in class||High quality||High quality|
AWS Vs Azure Vs Google Cloud: Pricing
The price factor is known to be the prime impetus that affects the decision-making of IT businesses when selecting a public cloud service provider. In terms of price and system model, the following contrast between AWS, Azure and GCP will aid you in your decision making:
|Smallest Instance||An instance would cost you about USD 69/month with 2 virtual CPUs and 8 GB RAM.||An instance would cost you about USD70/month with 2 virtual CPUs and 8 GB RAM.||It will cost you about USD52/month to load 2 virtual CPUs and 8 GB of RAM.|
|Largest Instance||The largest instance would cost you about USD 3.97/hour, which involves 3.84 TB RAM and 128 vCPUs.||It will cost you about USD 6.79/hour for the largest case, including 3.89 TB RAM and 128 vCPUs.||Largest instance that includes 3.75 TB RAM and 160 vCPUs will cost you around USD 5.32/hour.|
With pay-per-minute billing options, AWS and Azure deliver their cloud services, while GCP offers a pay-per-second billing option. In addition, GCP provides different discounts and customizable contracts to optimize the surge of demand.
Amazon Web Services (AWS)
A pioneer in cloud computing, Amazon was the first entrant to the market for cloud storage a decade ago, leading in terms of both the number of products and users, with AWS known to be the cloud service efficiency benchmark.
AWS provides a variety of applications for Infrastructure as a Service (IaaS) that can be divided into computing, databases, distribution and storage of information and networking.
Using server-less services such as Amazon Kinesis Feeds, Amazon SQS Queues and AWS Lambda Functions, AWS allows a seamless and scalable data collection flow. It provides organizations with the opportunity, among other items, to choose the framework for the web application, operating system, database and programming languages as needed.
Using AWS monitoring software such as AWS CloudTrail and Amazon CloudWatch for user behaviour tracking and AWS Config for resource inventory management and updates, cloud infrastructure resource use may be tracked.
AWS leads to substantial change in companies’ competitiveness and market growth. The dynamic architecture and default service limits that are set in line with typical user expectations are some of the disadvantages of AWS.
The Microsoft Azure platform is built to develop, launch and operate numerous networks and applications across a vast network of data centres operated by Microsoft. Computing, networking, data storage databases and performance are included in the Azure products.
Azure Site Recovery allows site-to-site replication and data recovery for VMs hosted on Azure itself to be coordinated by organisations of all sizes. In different data centre areas, Azure provides Zone Redundant Storage or data storage redundancy.
Azure ExpressRoute allows data centre access to Azure over a private connection without using the Internet, ensuring better security.
Azure now provides comprehensive networking features, including support for numerous site-to-site virtual network links, as well as the ability to link virtual networks to each other through various regions.
Using the Azure Machine Learning Studio, expert developers can write, test and deploy algorithms.
Google Cloud Platform (GCP)
GCP is an enticing alternative to both AWS and Azure with an elegant interface, reduced costs, preemptible instances and scalable computing possibilities. Google uses full-scale encryption, including traffic between data centres, on both data and communication networks. Sample and payment tuning, privacy and traffic control, cost-effectiveness, and machine learning are some of the fields where Google Cloud actively competes with AWS.
Although all the three cloud services provide discounts up to 75 percent with a pledge of one to three years, Google additionally provides a continuous usage discount of up to 30 percent for each instance form operating for more than 25 percent each month. AWS’ 1-year free trial, along with a free tier that is not time-limited, matched GCP’s credit of USD 300 over 12 months. The credit model of GCP is better suited to organisations that are new to cloud services. In terms of machine vision, natural language analysis and localization, Google provides many off-the-shelf APIs. Machine learning engineers can develop models based on the open-source TensorFlow deep learning library of Google’s Cloud Machine Learning Engine.
A Three-way Battle
Through analysing them using various criteria such as computing, storage, files, locations and metadata, the variations between the three main cloud providers can be seen.
Compute: AWS provides the Elastic Compute Cloud (EC2) that manages all computing resources by controlling pre-configured virtual machines that can also be configured by users as needed. In the other hand, Azure offers scale sets for virtual computers and virtual machines, while GCP provides the same features for the Google Compute Engine (GCE).
Databases: All major cloud providers provide various resources and service offerings relating to databases. The Relational Database Service (RDS) from Amazon supports large databases including Oracle and PostgreSQL and handles anything from upgrading to patching. The Azure SQL database provides Azure with SQL database handling functionality, while GCP is Cloud SQL.
Location: By providing the least possible route to the expected client base, AWS, Azure and GCP deliver great coverage around the globe and guarantee optimum application performance. Although Amazon has 77 zones of distribution, Azure has a presence in 60+ regions and Google in 33 areas, regularly adding newer regions.
It is apparent that each of them is distinctive in its own way and gives consumers diverse choices.
All the three cloud platforms provide excellent features. However, it is highly recommended that you choose the platform based on your needs, as each of them provides distinctive features and leads different domains. If you are confused about choosing the right platform, feel free to contact us. At Augmento labs, we provide the best and experienced team to take care of every technical need of your business so that it can bloom to its full potential.