Why AWS?

A big and useful advantage of the AWS cloud is its flexibility and openness along with its depth and breadth. AWS has evolved since 2006 and built out its suite of cloud services. The hybrid cloud strategy is an area where AWS falls short in. AWS continues to lead the way, in very broad terms, regarding maturity and providing the most flexible range of functionality. Unlike Microsoft, AWS, has proven to be dismissive about the advantages of all the on-premise private clouds.
It has achieved a tremendous head start on the competition. Also, AWS is made to be enterprise-friendly. Most organizations usually prefer to store their sensitive data within their own data centers, like those of the financial sector, with the usage of public clouds for various purposes. Audience also views AWS as being a complex vendor for its operational management.

Why Azure?

Azure possess Platform as a service (PaaS) capabilities, and this becomes its particular strength. Technically, Azure links well with primary Microsoft on-premise systems like the System Center, Windows Server and Active Directory. One important point to be noted is that Azure can be restrictive to some extent in comparison to AWS as AWS, for supporting various platforms, provides customers with enough options.
The famous Microsoft beholds a firm footing within many organizations. This is viewed as a significant pull for Azure, where Microsoft functions in assisting those companies transition to the cloud. If you aim to run anything under windows server, Azure might not be the most appropriate option.

Why Google Cloud?

Google cloud has technically focused on its go-to-market strategy in proving itself on innovative, smaller projects at large organizations and not on becoming a strategic cloud partner. The company certainly aims at backing machine learning tools. Google cloud has set an excellent track record as far as innovative cloud-native companies and open source community are concerned.

It has proved itself to be more than an AWS copycat with its Big Query analytics engine, and the Cloud Spanner distributed database for launching innovative features in the machine learning space.

Also, as compared to the other two platforms, Google Cloud has the smallest footprint of global instances.

Altogether, these three popular cloud platforms dominate each other space, and their background explains their technical approach to the world of cloud computing. This specific comparison will strongly underline their basic strengths along with their weaknesses.

Let’s start understanding and comparing these three amazing platforms by exploring them in terms of some important features such as:

Managed AWS, Microsoft Azure, and Google Cloud Platforms, smoothly provide some essential capabilities about flexible computing, networking and storing. All of these three are mutually public cloud elements which is auto scaling, along with compliance, and instant provisioning security purposes, self-service, and features regarding identity management.

All the three competitive spheres revolves around data analytics & visualization, and it is to be believed that Azure is the most remarkable in this arena.

• AWS- AWS, to a lot extent, across storage, greatly offers the most significant range of services, computing, analytics, and database, mobile along with developer tools, management tools, enterprise applications, networking, and security purposes.

• AZURE- As far as Azure is concerned, Azure offers a very useful and huge array of features, but they provide value addition by delivering some specific capabilities depending on various number of users.
• GOOGLE CLOUD- When we are talking about Google Cloud platform, on the contrary, is falling into Enterprise Computing. Google basically possess 3 crucial points in their solutions, which enlightens: Future-Proof Infrastructure, Very Powerful Data & Analytics and Server less, Just Code.
Machine-learning engineers building models technically are assisted by specific Cloud Machine Learning Engine provide by Google. Google also has abundance of complete host of off-the-shelf APIs, for tasks and activities like computer visions, translation, natural language processing.

Now let’s elaborate the technical functional features of these three cloud platforms in terms of Compute, databases, storage, and networking.

• AWS- This specific platform storage includes storage like Elastic Block Storage (EBS), Simple Storage (S3), and Import/Export large volume data transfer service, Elastic File System (EFS), Glacier archive backup and Storage Gateway, which keeps on integrating with on-premise environments.

• Azure- As far as we talk about Azure, the concept of Virtual Machines (VMs) is basically pictured in this platform. It also centrally revolves around other tools such as Azure Auto scaling service, Resource Manager, Cloud Services to provide assistance while deploying cloud applications.

• GOOGLE CLOUD- Google Cloud effectively delivers VMs in its data centers. This process is undertaken by the scalable Compute Engine of Google. Technically they come with the promise of consistent performance, stable disk capacity, and quick booting-up time, and are quite customizable depending on the needs of the potential customers.

AWS, Azure and Google Cloud in Terms of Pricing:

Generally, prices of these platforms are roughly comparable, especially because AWS shifted to by-the-second from by-the-hour, bringing it in line of competition with Google and Azure. But building an exact comparison is difficult as all of these three slightly offer variable discounts, pricing models and go frequent price cuts.

Azure’s pricing is more competitive in some spheres, be it Google or amazon, due to a proper plan to lead various definite segments of the cloud.

Google Cloud’s hosting pricing model competes directly with rivals, even as it emphasizes on its goal to bill depending exactly on resource usage.