AWS vs Azure vs Google

In the cyberspace, changes and upgrades are vital and the degree of adopting current trends as well as the capability to support future enhancements are the key goals of the cloud service providers. Due to the presence of Cloud Tech Giants in IT world, competition among them has led to a battle field of cloud where the vendors are trying to get more public attention by either dropping the prices or introducing new functionalities on existing cloud platforms.

In this article, we are going to gain an insight into the comparison among three cloud giants:-

·       Amazon Web Services (AWS)

·       Google Cloud Platform (GCP)

·       Microsoft’s Azure

To compare these giants, we will focus on the service types they are offering:-

1.    Computing efficiency

2.    Storage

3.    Networking infrastructure

4.    Pricing

Computing efficiency:-

AWS	GCP	Azure
Amazon’s core compute service :AWS’s EC2 (Elastic Compute Cloud)	Google’s core compute service: Google Compute Engine (GCE)	Introduced the compute service as a preview, and made available the service for general use on May 2013
Facilitates users to configure virtual machines using either pre-configured or custom AMIs (machine images).	Allows users launch virtual machines, much like AWS, into regions and availability groups.	Promptstheusers to choose a VHD (Virtual Hard Disk) to create a Virtual Machine.
Supports load balancing (ELB-EC2 Load Balancing) and auto scaling.	Supports load balancing and  extended support for Operating Systems	Load balancing by disk virtualization. User just needs to specify the number of cores and amount of memory

2.Storage:-

AWS	GCP	Azure
Offers ephemeral (temporary) storage which is allocated once an instance is started.It is destroyed after the termination of the instance.	Provides both temporary storage and persistent disks.	Uses temporary storage (D drive) and Page Blobs (Microsoft’s Block Storage option) for VM-based volumes.
Provides Block Storage ( equivalent to hard disks in PCs)	Primary storage medium:Google Cloud Storage.GCP supports relational DBs through Google Cloud SQL	Block Blobs and Files are used for Object Storage.
Offers object storage with S3 Service and archiving services with Glacier. Fully supports relational and NoSQL databases and Big Data.	Google Services: Big Query, Big Table, and Hadoop, are fully supported. Google’s Nearline offers archiving just like the AWS Glacier, but with virtually no latency on recovery.	Supports both relational and NoSQL databases, and Big Data, through Windows Azure Table and HDInsight.

3. Networking Infrastructure:-

AWS	GCP	Azure
Networking Component: Amazon’s Virtual Private Clouds (VPCs)	Networking Component: Google Compute Engine Subnets	Networking Component: Azure’s Virtual Network (VNET)
allow users to group VMs into isolated networks in the cloud	Compute Engine instance belongs to a single network, which defines the address range and gateway address for all instances connected to it.	allow users to group VMs into isolated networks in the cloud
users can define a  network topology, create subnets, route tables, private IP address ranges, and network gateways.	Firewall rules can be applied to an instance, and it can receive a public IP address.	users can define a  network topology, create subnets, route tables, private IP address ranges, and network gateways.
Supports Public IP	Supports Public IP	Supports Public IP
Supports Hybrid Cloud	No Support for Hybrid Cloud	Supports Hybrid Cloud
Supports Firewalls	Supports Firewalls	Supports Firewalls

5.    Pricing:

AWS	GCP	Azure
Charges customers by rounding up the number of hours used	charges for instances by rounding up the number of minutes used	charges customers by rounding up the number of minutes used for on demand
AWS instances can be purchased using any one of three models: on demand – customers pay for what they use without any upfront cost reserved – customers reserve instances for 1 or 3 years with an upfront cost that is based on the utilization spot – customers bid for the extra capacity available	Google recently announced new sustained-use pricing for compute services that will offer a simpler and more flexible approach to AWS’s reserved instances. Sustained-use pricing will discount the on-demand baseline hourly rate automatically as a particular instance is used for a larger percentage of the month.	Azure charges customers by rounding up the number of minutes used for on demand. Azure also offers short-term commitments with discounts.
Pricing Model: On demand, reserved, spot	Pricing Model: On demand – sustained use	Pricing Model: On demand – short term commitments (pre-paid or monthly)

Why AWS is better?

Scalability	·       High availability of on-demandstorage, bandwidth, and computational power. ·       Pay as per your use.
Costs	·       Works in a way that the marginal cost of an additional product keeps going down. ·       Less cost for adding more storage and bandwidth to your account
No-Commitment	·       Offers everything with absolutely no-commitment at all, not even a month. ·       All server-backed services are charged on hourly basis
Security	·       Data centers are staffed 24×7 by trained security guards, and access is authorized strictly on a least privileged basis ·       Multiple geographic regions and Availability Zones to combat with failure ·       Ability to configure built-in firewall rules
Flexibility	·       Auto scaling to build a self-managing infrastructure aligned closely to the actual need based on traffic/resources utilization. ·       Amazon Machine Images (AMIs) enable you to distribute clones
Global Leader	·       global presence with 10 regions, 36 availability zones and more than 50 edge locations
API	·       APIs available in various programming languages to manage the AWS infrastructure programmatically