Cloud Platform Comparison: AWS vs. Azure vs. Google Cloud

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AWS – With an exponentially growing toolset, Amazon’s capabilities are unmatched. However, its cost structure can be confusing, and its focus on public clouds rather than hybrid or private clouds means that interoperability with data centers is not a top priority for AWS.

Microsoft Azure – A formidable competitor to AWS with an incredibly powerful cloud infrastructure. If you're an enterprise customer, Azure speaks your language - few companies have an enterprise background (and Windows support) like Microsoft. Azure knows you're still running a data center, and the Azure platform strives to interoperate with data centers; hybrid cloud is the real advantage aws vs azure vs google cloud pricing.

Google Cloud - A well-funded underdog in the competition, Google entered the cloud market late and didn't have an enterprise focus to help attract enterprise customers. But its technical expertise is deep, and its industry-leading tools in deep learning and artificial intelligence, machine learning and data analytics are a distinct advantage.

Deep Cloud Comparison: AWS vs Azure vs GCP:

AWS, Azure, and Google: Overall pros and cons aws vs azure vs google cloud pricing
Each leading vendor has specific strengths and weaknesses that make them a good choice for certain projects - there is no "one size fits all" cloud solution aws vs azure vs google cloud pricing.

Advantages and disadvantages of AWS

Amazon's biggest advantage is its dominance of the public cloud market. Gartner states in its Magic Quadrant for Global Cloud Infrastructure-as-a-Service, "AWS has been the market share leader in cloud IaaS for over 10 years."

Part of its popularity is undoubtedly its vast reach. AWS has a large and growing number of available services and the most comprehensive global network of data centers. The Gartner report concludes, "AWS is the most mature enterprise-level vendor with the deepest ability to manage large numbers of users and resources aws vs azure vs google cloud pricing."

A big weakness for Amazon has to do with cost. While AWS regularly lowers prices, many businesses find it difficult to understand the company's cost structure and effectively manage those costs when running a large number of workloads on the service.

Overall, however, Amazon's advantages far outweigh these disadvantages, and organizations of all sizes continue to use AWS for a variety of workloads aws vs azure vs google cloud pricing.

Pros and cons of Microsoft Azure

Microsoft was a late starter in the cloud market, but by essentially taking its on-premises software (Windows Server, Office, SQL Server, Sharepoint, Dynamics Active Directory, .Net, etc.) and repurposing it to the cloud, it gave itself a Quick start.

A big reason for Azure's success: so many businesses deploy Windows and other Microsoft software. Because Azure is tightly integrated with these other applications, businesses that use a lot of Microsoft software often find it meaningful to use Azure as well. This builds loyalty for existing Microsoft customers. Additionally, if you're already an existing Microsoft enterprise customer, you can take advantage of significant discounts on service contracts.

On the other hand, Gartner considers some of the platform's flaws flawed. "While Microsoft Azure is an enterprise-ready platform, Gartner clients report that the service experience does not feel as enterprise-ready as they expected given Microsoft's long history as an enterprise vendor," it said. "Customers mention technical support, documentation, training, and the breadth of the ISV partner ecosystem."

Pros and cons of Google Cloud Platform

Google has a strong offering when it comes to containers, as Google developed the Kubernetes standard that AWS and Azure now offer. GCP focuses on high computing products such as big data, analytics, and machine learning. It also offers considerable scale and load balancing - Google knows datacenters and fast response times.

On the downside, Google's market share is a distant third, likely because it doesn't have a traditional relationship with enterprise customers. However, it is rapidly expanding its product and global data center footprint.

Gartner said its "customers typically choose GCP as a tier 2 provider rather than a strategic provider, although GCP is increasingly being chosen as a strategic alternative to AWS by customers whose businesses compete with Amazon and are more open source centric Or DevOps-centric, so not quite aligned with Microsoft Azure.

AWS Vs. Azure Vs. Google: Compute
AWS computes:

Elastic Compute Cloud: Amazon's flagship computing service is the Elastic Compute Cloud, or EC2. Amazon describes EC2 as "a network service that provides secure, resizable computing power in the cloud." EC2 offers a variety of options, including a wide variety of instances, support for Windows and Linux, bare metal instances, GPU instances, high performance computing, autoscaling, and more. AWS also offers a free tier for EC2 that includes 750 hours per month for up to 12 months.

Container services: In the computing category, Amazon's various container services are growing in popularity, with options to support Docker, Kubernetes, and its own Fargate service, which automates server and cluster management when using containers. It also offers a virtual private cloud option called Lightsail, Batch for batch computing jobs, Elastic Beanstalk for running and scaling web applications, and a few other services.

Microsoft Computing:

Virtual Machine: Microsoft Azure's primary cloud-based computing service is called a virtual machine. It supports Linux, Windows Server, SQL Server, IBM and SAP, as well as enhanced security, hybrid cloud capabilities and integrated support for Microsoft software. Like AWS, it has an extremely large catalog of available instances, including GPU and high-performance computing options, as well as instances optimized for artificial intelligence and machine learning. It also offers a free tier of 750 hours per month of a Windows or Linux B1S virtual machine for one year.

Additional Services: Azure's version of Auto Scaling is called a virtual machine scale set. Azure has two container services: Azure Container Service is based on Kubernetes, and Container Services is managed using Docker Hub and Azure Container Registry. It has a Batch service, a cloud service similar to AWS Elastic Beanstalk for scalable web applications. It also has a unique product called Service Fabric, designed for applications with a microservices architecture.

Google calculates:

Compute Engine: In contrast, Google's catalog of computing services is a bit shorter than that of its competitors. Its main service, called Compute Engine, has custom and predefined machine types, per-second billing, Linux and Windows support, automatic discounts, and a carbon-neutral infrastructure that consumes half the energy of a typical data center. It offers a free tier that includes one f1-micro instance per month for up to 12 months.

Focus on Kubernetes: Like all leading cloud providers, it offers containers and microservices well. Google provides Kubernetes Engine for organizations interested in deploying containers. Notably, Google has been actively involved in the Kubernetes project and has deep expertise in this area.

AWS, Azure and Google: Storage

AWS storage:

SSS to EFS: AWS's storage services include Simple Storage Service (S3) for object storage, Elastic Block Storage (EBS) for persistent block storage used with EC2, and Elastic File System (EFS) for file storage . Some of its more innovative storage products include Storage Gateway, which supports hybrid storage environments, and Snowball, a physical hardware appliance that organizations can use to transfer petabytes of data when Internet transfers are not feasible.

Databases and Archives Amazon has a SQL-compatible database called Aurora, Relational Database Service (RDS), DynamoDB NoSQL database, ElastiCache in-memory data store, Redshift data warehouse, Neptune graph database, and database migration service. Amazon offers Glacier, which is designed for long-term archival storage at a very low price. Additionally, its Storage Gateway can be used to easily set up backup and archive processes.

Azure Storage:

Storage Services: Microsoft Azure's basic storage services include Blob storage for REST-based object storage for unstructured data, queue storage for high-volume workloads, file storage, and disk storage. It also has a data lake storage, which is useful for big data applications.

Extensive database: Azure's database options are particularly extensive. It has three SQL-based options: SQL Database, MySQL Database, and PostgreSQL Database. It also has data warehouse services, as well as Cosmos DB and table storage for NoSQL. Redis Cache is its in-memory service and Server Stretch Database is its hybrid storage service designed for organizations using Microsoft SQL Server in their own data centers. Unlike AWS, Microsoft does provide actual backup services, as well as site recovery services and archive storage.

Google Storage:

Unified Storage and more: GCP offers a growing menu of available storage services. Cloud Storage, its unified object storage service, also has a Persistent Disk option. It provides transfer devices similar to AWS Snowball as well as online transfer services.

SQL and NoSQL On the database side, GCP has an SQL-based Cloud SQL and a relational database called Cloud Spanner, which is designed for mission-critical workloads. It also has two NoSQL options: Cloud Bigtable and Cloud Datastore. It has no backup and archive services.

AWS, Azure and Google: Key cloud tools
Looking ahead, experts say emerging technologies such as artificial intelligence, machine learning, the Internet of Things (IoT) and serverless computing will be key points of differentiation for cloud providers. All three leading suppliers have already begun experimenting with offerings in these areas, with the potential to expand their services in the coming year.

AWS key tools:

Sagemaker to Serverless: Like other areas, AWS has the longest list of services in these areas. Highlights include the SageMaker service for training and deploying machine learning models, the Lex conversational interface that also powers its Alexa service, the Greengrass IoT messaging service, and the Lambda serverless computing service.

AI and ML: Among its many AI-oriented services, AWS offers DeepLens, an AI-powered camera for developing and deploying machine learning algorithms for optical character recognition, image and object recognition, and more. AWS has released Gluon, an open source deep learning library designed to make it easy for developers and non-developers to build and quickly train neural networks without needing to know AI programming.

Azure key tools:

Cognitive Services: Microsoft is investing heavily in artificial intelligence, offering machine learning services and robotics services on Azure. It also features Cognitive Services, including the Bing Web Search API, Text Analytics API, Face API, Computer Vision API, and Custom Vision Services. For IoT, it has various management and analytics services, and its serverless computing services are called capabilities.

Support for MSFT software Not surprisingly, some of Azure's top tools are designed to support native Microsoft software. Azure Backup is a service that links Windows Server Backup in Windows Server 2012 R2 and Windows Server 2016. Visual Studio Team Services hosts Visual Studio projects on Azure.

Google Keytool:

Big AI: For Google Cloud Platform, AI and machine learning are areas of focus. Google is a leader in AI development thanks to TensorFlow, an open-source software library for building machine learning applications. The TensorFlowFlow library is popular and well respected. A testament to its popularity is the recent addition of TensorFlow support by AWS.

IoT to Serverless: Google Cloud offers robust offerings in APIs for natural language, speech, translation, and more. Additionally, it offers IoT and serverless services, but both are still in beta preview.

AWS, Azure and Google: Pricing
See also: A deep dive into AWS vs. Azure vs. Google's cloud service pricing.

Understanding the pricing of these three cloud leaders is challenging — and pricing is changing; it can also be based on what customers can do with them The service representatives quarrel with specific arrangements to make changes. Realize:

AWS Pricing: Amazon's pricing is particularly inscrutable. While it does provide a cost calculator, the sheer number of variables involved makes it difficult to get an accurate estimate. Gartner advises: "[Amazon's] granular pricing structure is complex; third-party cost management tools are highly recommended."

Azure Pricing: Microsoft Azure doesn't make things any easier. Due to Microsoft's use of complex software licensing options and situation-based discounts, it can be difficult to understand its pricing structure without outside help and/or extensive experience.

Google pricing: In contrast, Google uses its pricing as a point of differentiation. It is designed to offer "customer friendly" prices that are better than other suppliers' prices. Gartner notes that "Google uses deep discounts and extremely flexible contracts to try to win projects from customers who currently spend a lot of money with cloud competitors."

Key tip: Organizations that base their cloud vendor decisions primarily on price need to analyze each project on a case-by-case basis to get the best deal. And since suppliers regularly cut prices, they may need to revisit these calculations frequently.

AWS vs. Azure vs. Google: What's Right for You?
As mentioned at the beginning of this article, the best public cloud provider for you will depend on your needs and workload. In fact, the best supplier for some of your projects may not be the best supplier for your other projects. Many experts believe that most enterprises will invest heavily in multi-cloud. In fact, adopting a multi-cloud strategy may help reduce vendor lock-in or match workloads with the best available services.

AWS Choice: AWS has a rich set of tools and services and a massive scale, so you can't go wrong. The only reason not to choose Amazon is if you want a more personal relationship, what small boutiques can offer. At its size, it's difficult for Amazon to develop a close relationship with every customer, but there are managed service providers that can offer this kind of focused service.

Azure Choice: Microsoft's biggest draw, of course, is the Microsoft Store. All your existing .Net code will run on Azure, your server environment will be connected to Azure, and you will find it easy to migrate on-premises applications. Additionally, Azure's deep focus on hybrid cloud will help you connect legacy data center environments with the rapidly scalable (and feature-rich) Microsoft cloud.

Google Choice: Google is growing fast, but it's still a work in progress. Of course, the search giant has no traditional background in dealing with businesses. But it's wholeheartedly committed to its multibillion-dollar cloud computing effort. It's partnered with Cisco, which understands the business. The people who should be following Google now are people who saw it a year ago but didn't like what they saw. They might be surprised. Google built the cloud on its strengths, namely scale and machine learning. Obviously worth a look.

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