Comparing AWS vs Azure vs Google Cloud: Which Cloud Service Is Right for You?


The cloud computing market is growing at an exponential growth. It is set to become one of the top-most industries by 2030. Cloud platforms like Google Cloud, AWS, and Azure make up a combined 64% of the total market share, making these platforms the best in cloud computing. 

This article will go through these major cloud service providers, what they provide, how they differ from each other, their impact, and overall experience. 

What is Amazon Web Service?

Amazon Web Service (AWS) is a comprehensive and widely renowned cloud platform that offers 200 plus features from data centers worldwide. The platform is a combination of IaaS (Infrastructure-as-a-service, SaaS (Software-as-a-service), and PaaS (Platform-as-a-service). 

The platform was first established in 2006 and includes more than 200 services, including: 

  • Databases 

  • Storage 

  • Data management

  • Development tools 

  • Migration 

  • Networking

  • Compute 

What exactly is Azure and how does it work?

Azure is a public cloud computing platform that offers solutions for IaaS, SaaS, and PaaS. These can be used for services such as networking, storage, virtual computing, and much more.  

Azure depends on virtualization, like all other cloud platforms. Most of the computer hardware can be run in software emulations. Let’s take a deeper look at how Azure works:

These emulations help with mapping software instructions to hardware instructions. Since emulation layers allow the execution of virtualized hardware in software like the actual hardware itself. 

Moreover, physical servers in datacenters execute the virtualized hardware for customers. These servers are organized in racks and blades, a PDU, and a network switch. The racks are grouped into clusters. 

Then the chosen racks run virtualized hardware instances for users. Some servers run cloud management software too, known as a fabric controller. 

Each instance is connected to another set of servers running cloud orchestration software, called the front end. The front end contains the RESTful APIs, internal Azure databases. 

What is Google Cloud and why is it used?

Google Cloud provides client libraries where you can easily create and manage resources. The platform is a suite of public cloud computing services that also include a variety of hosted services for compute, application development, and storage. 

Some of the cloud computing products that Google Cloud offers include:

  • Google Kubernetes Engine (GKE)

    A management and orchestration system that runs within Google’s public cloud services. 

  • Google App Engine

    A PaaS based platform that offers software developers access to Google’s scalable hosting. 

  • Google Cloud Storage

    A cloud storage platform that stores large, unstructured data sets. 

Furthermore, Google Cloud offers application development and integration services. It also has higher-level services, such as Google BigQuery. 

AWS vs. Azure vs. Google Cloud: the key differences and similarities

All three cloud platforms have different offerings. `Azure provides efficient and scalable software solutions. AWS holds a firm grasp over cloud infrastructure, including networking, server, scalable storage, cybersecurity solutions, and mobile development. Google Cloud, or GCP, allows easy interaction with other vendor products and offers high-end big data analytics. 

Let’s review their key differences and similarities. 

a. Regions and availability

  • AWS is available in a variety of regions, which are widely dispersed into separate locations. 

  • Azure is deployed in locations where Microsoft operates datacenters. It’s generally available in 52 regions around the world with plans on expansion. 

  • Google Cloud services are available in locations across North and South America, Asia, the Middle East, Europe, and Australia. All locations are further divided into zones and regions. 

b. Features and tools

  • AWS has features and tools like Amazon S3 for scalable object storage, EC2, and Lambda – a serverless computing for code execution. 

  • Azure has blob storage, uses virtual machines for scalable cloud computing, and has functions like serverless compute service. 

  • Google Cloud offers global object storage, virtual machines, and has event-driven serverless functions. 

c. Compute Services

  • AWS provides EC2 for scalable computing power.

  • Azure's Virtual Machines cater to diverse workload requirements.

  • Google Cloud's Compute Engine offers flexibility and high-performance computing.

d. Database & Storage Services:

  • AWS's Amazon RDS and S3 are key for databases and storage.

  • Azure offers Azure SQL Database and Blob Storage.

  • Google Cloud provides Cloud SQL and Cloud Storage for similar functionalities.

e. Networking:

  • AWS has Amazon VPC for customizable networking.

  • Azure's Virtual Network enables secure connections.

  • Google Cloud's Virtual Private Cloud ensures isolated networking.

f. Hybrid and Multi-Cloud Capabilities:

  • AWS Outposts enables hybrid cloud deployment.

  • Azure Arc facilitates managing resources across environments.

  • Google Anthos offers a consistent platform across on-premises and cloud.

g. Specialized Services:

  • AWS boasts services like Lambda for serverless computing.

  • Azure's Cognitive Services offer AI capabilities.

  • Google Cloud's BigQuery excels in big data analytics.

h. Artificial Intelligence and Machine Learning:

  • AWS's SageMaker simplifies machine learning model development.

  • Azure's Azure Machine Learning enhances AI capabilities.

  • Google Cloud's AI Platform provides scalable machine learning solutions.

i. Pricing and Support:

  • AWS pricing is pay-as-you-go with various pricing models.

  • Azure follows a similar pay-as-you-go model with cost management tools.

  • Google Cloud offers sustained use discounts and personalized support plans.

What are the most common use cases for AWS vs Azure vs GCP?

  1. 1

    AWS Common Use Cases

    AWS can have use cases that include to efficiently host and scale web applications using services like Amazon EC2 and AWS Elastic Beanstalk.

    Another case is where users can store data with Amazon S3 and retrieve large amounts of data whenever required. 

  2. 2

    Azure Common Use Cases

    Azure can be used in various cases. Users can leverage its hybrid cloud deployments and integrate it with on-premises infrastructure and the cloud. 

    Another use case is where users can utilize AI and analytics with Azure’s machine learning capabilities for data analysis and attaining artificial intelligence solutions. 

  3. 3

    Google Cloud (GCP) Common Use Cases

    GCP offers data analytics with BigQuery that help to analyze large datasets and gain valuable insights. Users can also utilize TensorFlow to implement AI solutions for different Machine Learning use cases. 

Comparing the pros and cons of each cloud platform

1. Amazon Web Services (AWS)

Pros

cons

Extensive Service Offering

Can be complex for beginners

Market Leader

Pricing can be intricate and potentially costly

Global Data Center Presence

Learning curve for a vast array of services

Robust Security Features

Limited hybrid cloud capabilities

Strong Ecosystem and Community Support

Fewer enterprise-focused features compared to Azure

2. Microsoft Azure

Pros

cons

Seamless Integration with Microsoft Tools

Some services are still catching up to AWS

Hybrid Cloud Capabilities

Smaller global infrastructure compared to AWS

Enterprise Focus and Strong Compliance

Pricing can be higher in some cases

Extensive Set of Developer Tools

Steeper learning curve for certain services

Excellent Support for Windows-Based Apps

Fewer third-party integrations compared to AWS

3. Google Cloud Platform (GCP)

Pros

cons

Strong Emphasis on Machine Learning

Smaller market share compared to AWS and Azure

Competitive Pricing and Discounts

Fewer services compared to AWS and Azure

Global Network Infrastructure

Learning curve for users new to Google products

Strong Embrace of Open Source Technologies

Enterprise support still evolving

Emphasis on Scalability and Performance

Less mature ecosystem compared to AWS and Azure

AWS vs. Google Cloud vs. Azure: which cloud platform should I choose?

AWS, Azure, and GCP are well-known cloud providers, each has different qualities. 

AWS offers scalability and a wide reach globally, Azure has amazing security features and is great when integrated with other platforms, and GCP a variety of open-source technologies and has a strong focus on machine learning. 

When it comes to the market share, AWS has the maximum due to its high-end advanced solutions. 

What are the career prospects for AWS, Azure, and GCP cloud developers?

There are several career paths you can choose from after attaining certifications for each platform and gaining a bit of cloud computing experience. Some prominent roles include:

a. Amazon Web Services:

b. Microsoft Azure:

c. Google Cloud Platform:

Tips for starting Your Career in the Cloud Computing 

Once you have chosen your certification, it is important to focus on working your way to land a successful role in cloud computing. Here are some tips to help you get started:

  • Create a portfolio using projects from your knowledge and build a website to showcase your projects.

  • Build your network and make human connections with people.

  • Gain as many reputable references as you can, strong references can help you stand out.

  • Gain as much experience as you can through internships, training programs, or working with other people in the same career as you aspire to work in.

  • Be adaptable to the changing cloud technology landscape so your skillsets keep on improving.

Conclusion

AWS, Azure, and GCP collectively hold 64% of the cloud market share. AWS leads with an extensive service offering, while Azure integrates seamlessly with Microsoft tools.

GCP emphasizes machine learning. Differences in regions, features, and pricing cater to varied needs. 

Aspiring cloud developers can pursue roles based on platform-specific strengths that you can build according to your interests and stay adaptable to the changing landscape. 

About the author

Youssef

Youssef is a Senior Cloud Consultant & Founder of ITCertificate.org

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