AWS vs Azure vs Google Cloud: Which Cloud Services is better for Enterprises?

Since cloud computing was introduced, it has gained immense popularity with the market and the industries within. Initially, the question was whether cloud computing should be given preference. Now, the question is, which cloud platform deserves preference?

There are various cloud service providers in the market. But, the highest performing platforms are AWS, Google Cloud, and Azure cloud platforms. These cloud service providers offer the following advantages to the industries:

1. Enhanced resource management
2. Extended storage
3. Access data anytime remotely
4. Enhanced security

Amazon’s cloud platform is called AWS and is occupying the top place for a very long time. According to a Synergy Research and report from 2020, Amazon has maintained a strong position and has stably maintained its pace.

Microsoft offers a strong foot forward in SaaS and GCP for AI is going to be a steady competitor for years to come. When it comes to market share, according to the 2019 study, GCP has offered 83% of growth, while Azure gave 75% growth. Amazon’s AWS has maintained a steady pace at 41%.

For any company or organization looking to take up cloud services, the above figures could be overwhelming. Let us take a look at the comparison of the three top platforms with each other.

We can compare the platforms based on the following factors:

1. Market Share
2. Storage capabilities
3. Tool offering
4. Compute Features

AWS vs Google vs Azure Market Share in 2020:

According to Canalys reports from February 2020, AWS reserves 32.4% of market share, Azure reserves 17.6% of market share while Google Cloud has 6% of market share.

Storage Capabilities: Amazon Web Services (AWS) vs. Azure Market vs. Google Cloud:

As far as any cloud service is concerned, they offer good storage capabilities. Let us take a look at how each cloud platform offers storage capabilities:

AWS Storage System:

With Amazon Web Services (AWS), you can access a whole range of services like Simple Storage Services (SSS) for object storage, Elastic Block Storage (EBS) for persistent block storage, and Elastic File System (EFS) to store the files.

You can also access Storage Gateway to enable hybrid storage. Also, you get access to Snowball, which is a physical storage drive to be used in the absence of network connectivity.

For database and archives, with Amazon, you can use Glacier which is specially designed for long-term archive storage. With its storage Gateway, you can easily backup and archive the data.

Azure Cloud Platform:

With Microsoft Azure, you get Blob storage for REST-based object storage with unstructured data, Queue storage for large-volumed data, File and Disk storage, and Data Lake Store for huge applications.

Azure offers various database storage options. It includes three SQL-based options, Data Warehouse Service, Cosmos DB, and Table Storage for NoSQL, Redis Cache, and the Server Stretch Database which is specifically made for enterprises that access Microsoft SQL server for their own databases. Unlike AWS, Microsoft provides Backup Service, along with Site Recovery Service and Archive Storage.

Google Cloud Platform:

Google Cloud provides a unified object storage service that has a Persistent Disk option. It also provides Transfer Appliances like AWS Snowball, along with other online transfer services.

As far as databases are concerned, GCP has SQL-based Cloud SQL with a relational database called Cloud Spanner which is specially designed for mission-critical projects. It offers two No-SQL selections: Cloud Bigtable and Cloud Datastore. GCP does not provide backup and archive services.

Tool comparison for AWS, Azure, and GCP:

Cloud computing services offer various tools and resources for enterprises. Here, we will take a look at the tools offered by AWS, Azure, and GCP:

AWS Tools:

AWS has been a leading drive to bring Artificial Intelligence and the Internet of Things (IoT) to enable the organizations to use SageMaker to train the staff and deploy machine learning. It provides Lambda serverless computing environment and freedom to deploy apps from their serverless repository. AWS also lets you include the integration of a range of IoT enterprise solutions for enhanced customization.

Azure Tools:

Microsoft provides Cognitive Services along with the enhancement of artificial intelligence. Cognitive Services is a suite of API-supported tools that provide integration with on-premises Microsoft software and business applications.

Functions is the only serverless platform which is a platform driven by the events that orchestrate and manage complex workloads. Microsoft offers Edge in terms of IoT which can be used for management and business analytics.

Google Tools:

Google’s cloud-based enterprise benefits offer natural language translation and speech to transition global enterprise coordination to ML app development. It also provides a huge open-source library TensorFlow. Its IoT and serverless platforms are in the beta stage yet.

Computation Services: Azure vs. AWS vs. Google:

All the platforms come with their own set of benefits and bottlenecks which may vary according to the kind of requirement your enterprise has. Let us take a look at the comparison of computation services offered by the top three cloud platform leaders.

AWS Computation Features:

AWS provides Amazon Elastic Compute Cloud or E2C that offers high compatibility and an enhanced level of flexibility and optimization of the cost of the database. The cloud platform comes with enhanced scalability through which you can scale the services up or down according to the load of the projects. Also, new instances can be added within moments.

You can track your apps using AWS auto-scaling monitor to scale your capacity with respect to your current requirements without adding pads to the price. They offer 99.99% of availability with respect to their service level agreement (SLA).

Amazon Elastic Container Service (Amazon ECS) supports Docker containers through a series of API calls. You can begin or end the Docker-enabled applications, send a query to the application’s state, manage the IP address of the website, and access security groups. This also includes IAM roles, CloudWatch events, Cloud Trail logs, and Cloud Formation templates. It also offers an ECS registry feature and a container service for Kubernetes.

Other AWS Compute features include the following things:

1. AWS Beanstalk
2. Amazon Lightsail
3. AWS Serverless Application Repository
4. VMware Cloud for AWS
5. AWS Batch
6. AWS Fargate
7. AWS Lambda
8. AWS Outposts
9. Elastic Load Balancing

Microsoft Azure Computation Features:

Azure relies heavily on a network of virtual machines that enable computation solutions for development, testing, application deployment, and data center extension. It works on the basis of an open-source platform that offers compatibility with Linux and Windows Servers, SQL Servers, Oracle, and SAP.

You can also access a hybrid cloud model which blends on-premises and public clouds and you can integrate load balancing all over the world. Azure Kubernetes Service (AKS) is a serverless container system that allows the deployment of containerized applications. With this service, the management of the application also becomes faster.

It also offers enhanced Continuous Integration/Continuous Delivery (CI/CD) experience, security, and enterprise governance that unites diverse teams working within a virtual office setting on a single platform. Following are the other Azure compute features:

1. Platform-as-a-service (PaaS)
2. Function-as-a-service (FaaS)
3. Service Fabric
4. Azure Batch

Google Cloud Compute Features:

Google cloud offers specialization in Kubernetes containers and supports Docker containers. Google cloud compute services offer management of resources, app deployment which you can scale up or down in a real-time environment. You can also deploy code from Google Cloud, Firebase, or Assistant.

Other features include:

1. Google App Engine
2. Docker Container registry
3. Instant Groups
4. Compute Engine
5. The Graphics Processing Unit (GPU)
6. Knative

Conclusion:

When it comes to selecting a cloud platform for your enterprise or organization, choose the one that can fit your budget and offer you the right services. Also, analyze your organizational requirements to see which platform suits your requirements the best. Study all the features each platform offers and see which one can meet the requirements of your enterprise and then choose accordingly.