Azure vs. AWS: Cloud Comparison

Comparing Azure and AWS reveals key differences between the cloud latforms in Big Data, developer tools, IoT support and management options.

The competition between Azure and AWS has a lot riding on it: the cloud computing market continues to boom. IDC predicts that public cloud vendors will generate $96.5 billion in revenue this year, climbing to $195 billion by 2020.

Currently, Amazon Web Services (AWS) is the undisputed cloud leader, with more than 30 percent of the infrastructure as a service (IaaS) market according to Synergy Research Group. However, Microsoft Azure experienced 100 percent revenue growth during the second quarter, and now has a firm hold on second place with more than 10 percent of the market.

Earlier this year, Datamation compared AWS vs. Azure in some key categories like pricing structure, compute power, databases and storage, applications, containers and security services. This article follows up with a look at the latest announcements from the vendors, as well as a comparison of the support they provide for big data analytics, developers, mobile and Web apps, the Internet of Things (IoT) and cloud management.

Azure vs AWS: What's New

Azure and AWS continue to roll out new offerings at a staggering pace. In the month of August alone, AWS put out more than thirty announcements about various improvements to its cloud computing services. Among the more noteworthy were the availability of a new Quick Start deployment of Spinnaker, an open source continuous deployment tool created by Netflix; the expansion of the EC2 Container Registry to five more regions, including US West (N. California), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and EU (Frankfurt); a new Application Load Balancer for Elastic Load Balancing; and general availability for Amazon Kinesis Analytics.

Microsoft Azure doesn't put out press releases at quite such a frenetic pace, but it also made several announcements this summer. Microsoft Azure provided the live and on-demand streaming for NBC Olympics production of the 2016 games in Rio. Microsoft and GE announced a new partnership that bought GE's Predix industrial IoT platform to Azure. Azure launched a new N-Series of virtual machines, which it claims are the fastest GPUs in the public cloud, and Azure Security Center became generally available.

Azure vs AWS: Big Data Analytics

Big data has become a big deal for enterprises. A 2016 survey from NewVantagePartners found that only 5.4 percent of firms had no big data initiatives planned, while 62.5 percent already had big data projects in production.

To help with big data analytics initiatives, AWS and Azure offer very similar rosters of services. On its list, AWS has six different offerings. Amazon Elastic MapReduce (EMR) is its managed Hadoop framework that also supports Apache Spark and Presto. For real-time streaming, it offers Kinesis, which collects and analyzes large amounts of streaming data. Amazon Machine Learning makes it easy to create models and use predictive analytics, even for users who have limited experience with data science. Other popular AWS big data services include its Elasticsearch Service for search and analytics, Quicksight business intelligence, Redshift data warehouse and AWS Data Pipeline for data workflow orchestration.

Microsoft Azure offers eight different big data analytics services, many of them offering features comparable to the AWS services. Azure's Hadoop-based product, which also supports Spark, R, HBase and Storm, is called HDInsight. Like AWS, it also offers a streaming service, called Stream Analytics, and a Machine Learning service for predictive analytics.

Azure's other services include Data Lake Analytics and Data Lake Store, both of which can handle extremely large volumes of data; Data Factory data orchestration and management; Data Catalog for data source discovery; and Power BI Embedded, a newer tool that allows developers to embed interactive data visualizations in their applications. In addition, Azure has a whole separate category of intelligence services based on its Cortana Intelligence Service and Cognitive Services, which don't have counterparts at AWS. Among these are several APIs related to its Bing search capabilities. This could be an area of differentiation for enterprises interested in adding artificial intelligence capabilities to their applications.

Azure vs AWS: Developer Tools

When it comes to developer tools, Azure and AWS take slightly different approaches. Based on the tools and processes that Amazon's own internal engineering teams use, the AWS suite of Developer Tools focuses on supporting DevOps. The tools include CodeCommit, which stores code in private Git repositories; CodeDeploy, which automates code deployments; and CodePipeline for Continuous Delivery. In addition, AWS also offers a Command Line Interface (CLI) for controlling AWS services and writing automation scripts. Amazon also offers one non-DevOps tool – IDC, there are currently 13 billion connected "things," a number that will likely skyrocket to 30 billion by 2020, generating $1.7 trillion in revenue.

To help their customers take advantage of that opportunity, Azure and AWS both offer IoT-related cloud computing services. Amazon's is called AWS IoT, and it promised that it can "reliably scale to billions of devices and trillions of messages." It includes tools for connecting devices to each other and to AWS cloud services, for securing data, and for processing and analyzing IoT data.

Azure has an IoT Suite that includes solutions for popular scenarios like remote monitoring and predictive maintenance. It also offers hubs for monitoring IoT deployments, streaming analytics, push notifications and machine learning capabilities that integrate with its cloud-based IoT services.

Azure vs AWS: Cloud Management

As enterprises move more workloads to the cloud, being able to manage and orchestrate those workloads easily is becoming more of a concern. In keeping with its focus on DevOps, AWS offers a long list of tools that automate common IT tasks for cloud computing environments. Those tools include CloudFormation for automated infrastructure provisioning, OpsWorks for Chef-base configuration management of cloud and on-premise workloads, CloudWatch for monitoring and dashboards, Config for resource inventory and configuration change tracking, CloudTrail to monitor user activity and API calls, Service Catalog to help organizations create their own self-service IT catalogs and Trusted Advisor for resource optimization recommendations.

Azure's list of cloud management tools is a little shorter. It includes the Microsoft Azure portal for managing and monitoring cloud-based applications, a scheduler for recurring workloads, the Operations Management Suite for managing hybrid environments, Process Automation and Log Analytics.

AWS pricing calculator

When comparing Azure and AWS, many cloud buyers use a pricing calculator like that offered by AWS.

Azure vs AWS: Making a Choice

So which cloud computing platform is right for your organization? Both Azure and AWS offer large and growing catalogs of services that can help enterprises capitalize on trends like big data analytics, IoT and mobility. Areas like developer tools and management tools offer more differentiation but again a lot of overlap, making the decision process difficult.

Fortunately, both services offer free or very inexpensive tiers for their cloud services, making it possible for enterprises to try them both out before they buy.

Also see: Amazon AWS vs. Microsoft Azure Buying Guide




Tags: cloud computing, AWS, Azure, Azure vs. AWS


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