14 ways AWS beats Microsoft Azure and Google Cloud

14 ways AWS beats Microsoft Azure and Google Cloud

Microsoft Azure and Google Cloud have advantages, but don’t match the breadth and depth of AWS

Andy Jassy (CEO - AWS)

Andy Jassy (CEO - AWS)

Credit: AWS

There are many good cloud companies that do a perfectly good job. You click and they deliver a root login to a running instance.

All of them are good. Some even have areas where they’re the best. None of them, though, manage to measure up to the breadth and depth of Amazon Web Services (AWS).

The reason is simple: AWS has built out so many products and services that it’s impossible to begin to discuss them in a single article or even a book. Many of them were amazing innovations when they first appeared and the hits keep coming

Every year Amazon adds new tools that make it harder and harder to justify keeping those old boxes pumping out heat and over-stressing the air conditioner in the server room down the hall.

For all of its dominance, though, Amazon has strong competitors. Companies like Microsoft, Google, IBM, Oracle, SAP, Rackspace, Linnode, and Digital Ocean know that they must establish a real presence in the cloud and they are finding clever ways to compete and excel in what is less and less a commodity business.

These rivals offer great products with different and sometimes better approaches. In many cases, they’re running neck and neck with AWS. And if what you’re after is a commodity machine, well, their commodity Linux instance will run the same code as AWS.

Sometimes the competitors not only match AWS for commodity products, but they actually do a better job. These advantages often appear when the competitors link their cloud to parts of the computer ecosystem that they already dominate.

If you want to use .NET code, you’ll find it just a bit easier on Microsoft Azure. If you want to use Google’s G Suite of web-based office productivity tools, it’s no surprise that they’re well-integrated with Google Cloud Platform.

Still, for all of these competitors’ innovation and success, Amazon continues to outshine them in many ways—and the words “many ways” is a pretty good summary of Amazon’s approach. The company has evolved a strong, consistent style that might be described as overwhelming.

The AWS cloud offers at least 10 different databases and another nine different products lumped in a separate category called “storage.” There are dozens of different types of machine available in dozens of different configurations of RAM and CPUs and you can arrange for Amazon to scale them automatically when the load increases.

Indeed, the greatest advantage of AWS may be the sheer overwhelming number of options. Most of the time, someone there has faced the same problem that’s confounding you and they’ve set up a team to productise a solution. You just have to work your way through all of the options.

Here are just 14 of the ways AWS beats Microsoft Azure and Google Cloud.

1 - Neutrality

Amazon is great at so many things, but there are a number of important parts of the computing ecosystem where they really don’t have a dog in the fight. In these areas, they’re good about playing well with everyone.

Microsoft Office dominates many business spaces around the world and Google’s G Suite handles most of the others. It’s common to find that the various parts of the AWS cloud like Alexa for Business work well with both worlds. Microsoft’s Visual Studio has many devotees and so does Eclipse. AWS doesn’t play favourites and has an integration toolkit for each of them.

Amazon is not afraid of embracing standards and bringing them inside its big tent. If you run Microsoft SQL Server or Oracle Database, Amazon will provide what you need and won’t force you to rewrite your code to use its own proprietary storage model.

It’s easy to find the products of ostensible competitors running smoothly in the AWS cloud. The company’s breadth and depth is a result of being unafraid of reaching into many corners of the computing world and excellent at bringing those corners into the cloud.

2 - Full-service options

In the early years, AWS was aimed at delivering commodity machines that did everything that was asked of them. Lately Amazon has been adding built-out services that target certain niches—like a customer service call centre, in the case of Amazon Connect.

Maybe you don’t need Amazon Connect, but as AWS adds more of these targeted services, there’s a good chance that someone at AWS already built most of what you need.

They’ve already got plenty of tools for call centres, Internet of Things, mobile app support, business productivity, and, for those with their own network of orbiting satellites, a full-function “Ground Station as a Service.”

3 - Container focus

All of the cloud companies understand the attractiveness of containers like Docker, but Amazon is pushing further by building a special, stripped-down version of Linux called Bottlerocketthat has just enough code to keep the machine running but not much more.

Teams running microservices can choose it and quit worrying about extra cruft like FTP servers sitting around in the background. Amazon also intends to embrace containers even more by skipping over the traditional packages for security and feature upgrades.

These will be available as complete containers instead, so upgrades can be done in one step and managed with many of the same tools you’re already using to juggle your own containers.

4 - AWS Lambda

AWS Lambda started as a cute idea, a kind of simple shell script that could glue together all of the operations in the cloud. Users quickly turned to Lambda’s serverless functions to handle occasional computing tasks because it’s so much more efficient than dedicating a machine for work that arrives sporadically.

That might be a background process that runs once an evening, a corner of your microservices architecture that isn’t used often, or maybe just that blog full of your rantings that still hasn’t found its audience yet.

Eventually people realised that Lambda could be ideal for more complicated background processing, especially the kind that would run sporadically. If a server is idling more than it’s working, switching to the serverless model could save a dramatic amount of money.

AWS noticed and expanded the maximum RAM for Lambda functions to 3GB and maximum running time to 15 minutes.

If your processing is sporadic, Lambda could be the cheapest way to host some significant jobs in the cloud. And the use cases will only continue to grow. AWS Lambda functions could already manipulate most parts of the Amazon cloud and they’re infiltrating what’s left. Amazon probably won’t stop until every part of the AWS cloud will answer to the serverless commands.

5 - Broad AI platform

If your shop is obsessed with mixing AI into your stack, Amazon has almost too many options to consider. There are too many to list. They begin with basic tools like SageMaker for training models to respond to your data. These tools have attracted plenty of developers and that may be why the sales literature brags that “85 per cent of TensorFlow projects in the cloud run on AWS.”

The basic training, though, is just the beginning because AWS also offers a wide range of tools aimed at particular industries. Amazon Comprehend Medicalplows through unstructured medical texts looking for lifesaving treatments. Amazon Fraud Detection looks for malicious behaviour.

Developers new to AI can begin exploring with highly automated options like AutoGluon, a project from the AWS lab that is designed to make it simpler to dive in.

The Microsoft and Google clouds also have deep AI expertise and commitment, but Amazon’s wide range is hard to beat.

6 - 24 terabytes of RAM

If you’re running very big enterprise databases or you just believe that whoever dies with the most RAM wins, some of the new high-memory machines from Amazon are just what you need. Up to 24 terabytes of RAM can be yours in just a few clicks.

AWS gives you other ways to wear your big boy pants as well. They’ve worked with vendors like SAP to make sure their cloud instances can scale up as big as necessary. Are your Oracle databases getting too big? Amazon wants to host them and it has expanded its Amazon RDS for Oracle machines to support instances with as much as 64 terabytes of SSD storage.

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Tags MicrosoftazureAmazon Web ServicesAWSGoogle Cloud

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