In our earlier blog posts, we’ve covered many Azure features, highlighting its PaaS capabilities and touching on some of the artificial intelligence services (Cognitive Services APIs) and how the Azure platform offers a rich ecosystem for businesses to host, scale, manage and easily provision services in the cloud.
In this blog post, we compare Amazon Web Services and Microsoft Azure, and we look at the key features both computing platforms have to offer. By the time you’re done reading, you’ll have a better understanding of both AWS and Azure.
Computing, Storage, and Databases
Most of the resources you provision in the cloud revolves around three main areas: computing, storage, and databases. Both Amazon Web Services and Microsoft Azure let you provision all three resources, but let’s look at these in more detail.
Computing instances are the virtual servers that host the applications that you need to run. With Amazon, these computing instances are called Elastic Compute (EC2) whereas in the Azure realm they are known as Virtual Machines (VMS).
AWS and Azure do well in this category, and both support Windows and *NIX images. Azure has a slightly higher CPU count, but both offer everything you will need which places both platforms on an even keel for the “compute” category.
Running services in the cloud involve processing data which must be saved at some point. AWS’s storage mechanism is called Simple Storage Service (or S3), and Microsoft Azure’s is called Blob Storage.
Both AWS and Azure are strong in this category and take care of the basics, including features like REST API access and server-side data encryption. AWS has some added handy features, for example, you can auto-bill customers that use your storage service – ideal if you have a SaaS product.
Most modern software applications need a database to save information, and AWS and Azure let you provision database services, whether you need a relational database or NoSQL offering; both platforms have you covered.
AWS is dubbed RDS (Relational Database Service), and Azure’s offering is called SQL Server. At the time of writing, AWS offers multiple database instances such as MySQL, MariaDB, SQL Server and Aurora.
While AWS may have more instance types you can provision and offers slightly more control over your DB instances; there’s no getting away from it, Azure tooling and interface makes it easy to perform DB operations.
This is where Azure really shines, especially for professionals that are invested in Microsoft Tooling such as Visual Studio. From Visual Studio you can connect to Azure services such as chatbots and debug remotely from your local codebase.
Publishing web projects and services are done in just a few clicks under the hood, and all required Azure instances will be set up for you. Azure also integrates nicely with Active Directory which is another great bonus.
AWS has welcomed the integration of open source technologies into their infrastructure whereas Microsoft has traditionally been “closed off” here – this has been changing in recent years, but with this in mind, you might find that open source software plays a little easier with AWS.
Machine Learning and Artificial Intelligence
In recent years we’ve seen the democratization of complex machine learning algorithms (Machine Learning as a Service – MLaaS) in the form of new online products and services. No longer do you need a Ph.D. to undertake natural language processing (NLP) or to identify human emotions in a set of images.
Both AWS and Azure offer a similar range of API driven services that allows you to add cognitive intelligence to your applications out of the box. For example, these services can be consumed via REST APIs making it simple for developers to extend your existing software products.
Just some of the areas in which cognitive intelligence can be added, include, but are not limited to:
- Vision and Image Recognition
- Text Classification
It should be noted that Azure offers slightly more features and services in this area, such as Spell Checking, Part of Speech Tagging, and Voice Verification, but with that said, both AWS and Azure support key machine learning features such as sentiment analysis and entity extraction.
Is there a winner?
This is a hard question to answer and ultimately depends on your unique business requirements. Amazon was initially ahead with their AWS platform, but Microsoft has closed the gap.
For businesses, especially software development firms that are heavily invested in the .NET or Microsoft stack, Azure is probably the more sensible option.
Both offer a wide array of tooling and services and continue to grow from strength, as AWS and Azure continuously increase their infrastructure. This will also help to provide economies of scale that ultimately will pave the way for price cuts for the business community.
In this blog post, we’ve looked at how Amazon Web Services and Microsoft Azure stack up against each other. By running through these examples, we hope you’ll have a better understanding as to which platform to adopt. If you’d like more information or are looking for guidance, then feel free to contact our sales team!