Public Cloud War: AWS vs Azure vs Google

AWS vs Azure vs Google

The competition is heating up in the public cloud space as vendors regularly drop prices and offer new features. In this article, we will shine a light on the competition between the three giants of the cloud: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft’s Azure.  While AWS has a significant head start on the others, Google and Microsoft are far from out of the race. As of today, March 23rd, 2016  Google is planning 12 new cloud data centers in next 18 months. They’ve both got the power, money, technology, and marketing to attract individual and enterprise customers. Let’s compare these three big players by service category: compute, storage, networking, and pricing structure.

public cloud

AWS vs Azure vs Google: cloud players


AWS vs Azure vs Google: Compute

AWS’s EC2 (Elastic Compute Cloud) provides Amazon’s core compute service, allowing users to configure virtual machines using either pre-configured or custom AMIs (machine images). You select the size, power, memory capacity, and number of VMs and choose from among different regions and availability zones within which to launch. EC2 also allows load balancing (ELB) and auto scaling. ELB distributes loads across instances for better performance, and auto-scaling allow users to automatically scale available EC2 capacity up or down.

In 2012, Google introduced their computing cloud service: Google Compute Engine (GCE). Google Compute Engine lets users launch virtual machines, much like AWS, into regions and availability groups. However, GCE didn’t become available for everyone until 2013. Since then Google has added its own enhancements, like load balancing, extended support for Operating Systems, live migration of VMs, faster persistent disks, and instances with more cores.

Also in 2012, Microsoft introduced their compute service as a preview, but didn’t make it generally available until May 2013.  Azure users choose a VHD (Virtual Hard Disk), which is equivalent to Amazon’s AMI, to create a VM. A VHD can be either predefined by Microsoft, by third parties, or be user-defined. With each VM, you need to specify the number of cores and amount of memory.

Table1 shows Big Three compute options:

Instance FamiliesInstances typesRegionsZones

Table1: AWS vs Azure vs Google: Compute

AWS vs Azure vs Google: Storage and databases

AWS provides ephemeral (temporary) storage that is allocated once an instance is started and is destroyed when the instance is terminated. It provides Block Storage that is equivalent to hard disks, in that it can either be attached to any instance or kept separate. AWS also offers object storage with their S3 Service, and archiving services with Glacier. AWS fully supports relational and NoSQL databases and Big Data.

Google’s Cloud Platform similarly provides both temporary storage and persistent disks. For Object storage, GCP has Google Cloud Storage. GCP supports relational DBs through Google Cloud SQL. Technologies pioneered by Google, like Big Query, Big Table, and Hadoop, are naturally fully supported. Google’s Nearline offers archiving as cheap as Glacier, but with virtually no latency on recovery.

Azure uses temporary storage (D drive) and Page Blobs (Microsoft’s Block Storage option) for VM-based volumes. Block Blobs and Files serve for Object Storage. Azure supports both relational and NoSQL databases, and Big Data, through Windows Azure Table and HDInsight.

Table2 shows a comparison of the three clouds in storage and DBs. 

Ephemeral (Temporary)Block StorageObject StorageRelational DBArchivingNoSQL and Big Data
AWSYesEBSS3RDSGlacierDynamoDB, EMR, Kinesis, Redshift
GCPYesPersistent disksGoogle Cloud StorageGoogle Cloud SQL NearlineCloud Datastore, Big Query, Hadoop
AzureTemporary Storage – D DrivePage BlobsBlock Blobs and FilesRelational DBsWindows Azure Table, HDInsight

Table 2: AWS vs Azure vs Google: Storage and databases

AWS vs Azure vs Google: Networking

Amazon’s Virtual Private Clouds (VPCs) and Azure’s Virtual Network (VNET) allow users to group VMs into isolated networks in the cloud. Using VPCs and VNETs, users can define a  network topology, create subnets, route tables, private IP address ranges, and network gateways. There’s not much to choose between AWS vs Azure on this: they both have solutions to extend your on-premise data center into the public (or hybrid) cloud. Each Google Compute Engine instance belongs to a single network, which defines the address range and gateway address for all instances connected to it. Firewall rules can be applied to an instance, and it can receive a public IP address.

AWS is unique in providing Route 53, a DNS web service.

Table 3 compares the three clouds from a networking point of view.

Virtual networkPublic IPHybrid CloudDNSFirewall/ACL
AWSVPCYesYesRoute 53Yes

Table 3:  AWS vs Azure vs Google: Networking

AWS vs Azure vs Google: Pricing Structure

AWS charges customers by rounding up the number of hours used, so the minimum use is one hour. AWS instances can be purchased using any one of three models:

  • on demand – customers pay for what they use without any upfront cost
  • reserved – customers reserve instances for 1 or 3 years with an upfront cost that is based on the utilization
  • spot – customers bid for the extra capacity available

GCP charges for instances by rounding up the number of minutes used, with a minimum of 10 minutes. Google recently announced new sustained-use pricing for compute services that will offer a simpler and more flexible approach to AWS’s reserved instances. Sustained-use pricing will discount the on-demand baseline hourly rate automatically as a particular instance is used for a larger percentage of the month.

Azure charges customers by rounding up the number of minutes used for on demand. Azure also offers short-term commitments with discounts.

Table 4 shows the comparison in Pricing and Models between the three public clouds.

AWSPer hour – rounded upOn demand, reserved, spot
GCPPer minute – rounded up (minimum 10 minutes)On demand – sustained use
AzurePer minute – rounded up commitments (pre-paid or monthly)On demand – short term commitments (pre-paid or monthly)

Table 4: AWS vs Azure vs Google: Pricing and Models

All this isn’t to say that there aren’t many other ways to compare the three giants, like support levels, management, security and access. However, this is a pretty good start. Cloud Academy remains vendor-neutral and offers learning paths, courses, quizzes, and hands-on labs for these competing services. Cloud Academy offers a free 7-day trial so readers may evaluate the content and quality of their learning resources.

Feedback means everything to us. We listen and react to your comments in shaping our offerings. Fairly recently, we added Learning Paths to our professional educational offerings. Learning paths guide students through a personalized learning experience. Each path is constructed as a specific track that brings a student’s knowledge to the next level, step by step.

The public cloud war drags on.  As cloud computing is still in an early, maturing stage, no one can predict exactly how things will change in the near future. But what we can say, is that prices will continue dropping and attractive features will continue appearing. Cloud computing is here to stay and the way we all use computers will follow along with it.

Motasem Aldiab

Motasem Aldiab

Motasem Aldiab is a professor, consultant, trainer, and developer. Dr. Aldiab has got his PhD in Computer Engineering from QUB in 2008. He is a certified trainer for the Cloud School and SOA School. He has been training and offering consultations for years in Java, SOA, and Cloud Computing, and leading workshops and training session (virtual or instructor led).

More Posts

Follow Me:

  • Eric

    I was expecting a deep dive into the various differences, pros and cons, of each service. However, I have to admit that I was disappointed by the article. At most it was a cursory overview of the services, and it made it seem as if it was all rainbows and unicorns.

    The section on networking was just laughable. Networking differences between AWS, Google, and Azure, could not be more different, but you just glazed over it as if they were all created equal.

    • Why don’t you post your more useful insights and opinions instead of dissing what is at least available in this article.

  • Sahel

    I found this article very useful. Especially, It is of much importance for beginners. It would be also interesting to see you publish more articles on big data and security. Best luck.

  • Motasem Aldiab

    This article is meant to give an overview of the big picture of the competition between the big three public clouds. We are already aware that we can dig deeper and focus more on each service pros and cons, however, that requires several articles and can’t be covered in one article. Some of these articles are already proposed and will appear on CA’s blog in the near future. Thanks for all who gave feedback whatever it is. We promise to deal with it in a positive sense and spirit.

  • msweetland

    great article–thanks

  • Esther Levine

    An engaging introduction, I look forward to the next posts as you delve deeper into the issues and cover additional topics as these services evolve. For those looking for a comparison about how some of the cloud providers handle data security and access management, you can find info in the FortyCloud post IaaS Security State of the Industry, which will soon be updated to include more cloud providers.

  • Devman

    Unfortunately outdated in many ways.

    Google Cloud Platform:

    Missing Features in the article:

    Instance types: 18

    Archival storage: Nearline

    NoSQL: BigTable, 120 open source solutions as click to deploy

    BigData: Dataflow (streaming and managed processing) Pub/Sub (realtime many to many messaging), 120 open source solutions as click to deploy

    Hybrid Cloud: VPN

    DNS: Google Cloud DNS

    Pricing after the latest pricecut (including TCO calculator):

    Not to mention the whole container story and other very interesting projects around analytics and machine learning.

    I guess there is a lot I missed, maybe also from other providers. Just wanted to inform that this resource is unfortunately not nearly up to date.

  • David

    Ummm… You seem to have left out the largest provider, IBM. Surely an expert in public cloud offerings like yourself is familiar with SoftLayer?

    • jerrymcguire12

      Ummm, softlayer isn’t even a blip on the radar between azure and aws. Aws alone is larger than its 11 nearest competitors.

    • Gus Smith

      As a user and non-expert, I’ve only heard about AWS, AWS and AWS. And a bit of Google and Azure.

  • Barbara C. Smith

    Great article Motasem! I am working on an executive overview that I need to present to my manager, can anybody point me to some other high-level discussions on this topic, I’m not a great writer (except when it comes to code :)) and I would like to see how some people describe it in a way that’s easy for non-technical folks … Thanks

  • lyoneel

    This is SO outdated, google DNS, lot of instances and custom instances for GC, Azure has hadoop

    This article is “AWS Centric” or fanboy.

    Reading a little more, maybe is because you sell AWS Certs? :/

    • Hi @lyoneel:disqus, please note that the article was published in March 2015 and It’s not been updated since then.

  • Dheeraj Sharma