The migration of enterprises to cloud computing continues at an astonishing rate. Companies are increasingly seeking out the benefits offered by cloud technologies above and beyond on-premise deployments.
The cloud computing market is now a vast ecosystem of providers, technologies, products, and services. Gartner forecasts the worldwide public cloud services market alone will grow by 17% to reach $266.4 billion.
|Cloud Business Process Services (BPaaS)||41.7||43.7||46.9||50.2||53.8|
|Cloud Application Infrastructure Services (PaaS)||26.4||32.2||39.7||48.3||58.0|
|Cloud Application Services (SaaS)||85.7||99.5||116.0||133.0||151.1|
|Cloud Management and Security Services||10.5||12.0||13.8||15.7||17.6|
|Cloud System Infrastructure Services (IaaS)||32.4||40.3||50.0||61.3||74.1|
Worldwide Public Cloud Service Revenue Forecast (Table Source: Gartner) Note: Totals may not add up due to rounding.
Among the 1000s of providers, a handful of technology companies have established themselves as household names in the world of cloud computing. When we think about cloud providers – Amazon Web Services, Google Cloud Platform, and Microsoft Azure are the three industry giants that spring to mind.
Today, we are going to compare two of these cloud giants: Google Cloud vs Azure, having already compared Google Cloud vs AWS in a previous article.
In this guide, we’ll cut through the complexity that surrounds cloud technology, explaining everything in layman’s terms to make it as accessible as possible.
Here at Kinsta, we exclusively utilize the Google Cloud Platform, but we’ll be providing you with an unbiased opinion.
Why Google Cloud vs Azure
If you are considering a move to the cloud, it is impossible to research cloud service providers and not uncover Google Cloud and Microsoft Azure as part of that exploration.
Even before the inception of cloud computing, both Google and Microsoft were globally recognized leaders in the technology space. Although delivering different products and services, these cloud giants are renowned for expertise, innovation, and excellence in both hardware and software. It is on this foundation that they have built their cloud platforms to dominate competitors.
In 2019, Gartner announced Google and Microsoft in their Magic Quadrant as leaders for cloud Infrastructure as a Service (IaaS) worldwide. With Amazon Web Services being the only other provider to share this accolade.
They earned their position as leaders by superiority in both axes of ‘Completeness of Vision’ and ‘Ability to Execute’ within the IaaS space.
Google Cloud and Microsoft Azure Continue to Grow
Whether you’re looking at IaaS, SaaS, or PaaS solutions, Google Cloud and Azure offer 100s of market-leading cloud products and services to choose from. A list that continues to expand as they innovate and evolve to offer greater and more numerous solutions.
Both Google and Microsoft feature in the top 5 public cloud infrastructure providers, who make up 80% of the IaaS market, according to data from Gartner.
These cloud tech giants continue to expand their customer base and both report impressive revenue growth throughout 2019. With figures suggesting the cloud providers are not only keeping pace with Amazon Web Services – the leading cloud provider – but actively taking market share away.
Google Cloud Platform Revenue in 2019
In the first half of 2019, Google reported impressive growth through its financial reports for Q1 and Q2. Despite a lack of clarity in the financial contribution of Google’s cloud services to overall revenue, Google CEO Sundar Pichai reported the company was on track to achieve an annual revenue run-rate of $8 billion from the Google Cloud Platform. An astonishing 100% increase from an annual run-rate of $4 billion at the same point in 2018.
Although Google fell far short of Wall Street’s expectations for company-wide revenue in its Q3 financial report, the business continues to report impressive growth in its cloud services. With these figures suggesting Google continues to take market share away from Amazon Web Services. And with AWS only reporting a 35% growth in AWS cloud revenues over the same period.
During their Fourth Quarter 2019 Financial Results Conference Call, Pichai announced Google’s continued cloud revenue growth.
If you want to know more, make sure you check out our in-depth Google Cloud Platform Market Share guide to know more.
Microsoft Azure Revenue in 2019
When looking at revenue from Microsoft Azure cloud services – like with Google – it is difficult to uncover the actual contributions. The business continues to provide a lack of transparency, reporting its Azure revenues within an ‘Intelligent Cloud’ grouping. It also masks it’s SaaS products – like Office 365 and Dynamics 365 – as part of a ‘Productivity and Business Processes’ revenue grouping.
Transparency aside, the tech giant is showing impressive growth in 2019. Comparatively – over the same time period as Google – Microsoft announced Azure revenue growth in excess of 60% over Q1, Q2, Q3, and Q4.
While consistent Azure revenue growth of 60% ensures Microsoft is also taking market share from Amazon Web Services, they continue to lose ground to the Google Cloud Platform.
Google Cloud vs Azure Features Comparison
The task of comparing and contrasting Google Cloud vs Azure features can be both difficult and time-consuming. Each provider now offers in excess of 100+ cloud products. Even if they offer the same service, it has a different name for their comparative product. Making it easy to get lost in the details.
Thankfully, the two platforms are very similar, with Google Cloud Platform and Azure Platform products grouped into the same categories. To save you time, and provide clarity, we have done the hard work of comparing most popular products from key categories.
In this section, we’ll cover the foundations of a cloud deployment including compute, storage, networking, and security. All of which we utilize here at Kinsta to deliver our state-of-the-art scalable WordPress hosting for our clients. Which helped us become one of the fastest-growing WordPress hosts in Europe and America.
So, let’s get started:
In this first category of compute, we’ll be focusing on virtual machines (VMs). Comparing and contrasting the setup of Microsoft Azure and Google Cloud Platform.
At a glance, each provider adopts a similar approach to VMs, which form a fundamental part of any cloud environment, and will run almost every type of customer workload you can think of.
The cloud giants have different naming conventions for VMs. They are known as Azure virtual machines on Microsoft Azure and Compute Engine on the Google Cloud Platform. Both providers also use differing high-level terminology and concepts.
To ensure clarity in comparison, Google mapped the differentiations for Azure and Compute Engine, which you can see in the table below:
|Virtual machines||Virtual machines||Virtual machine instances|
|Images||Image (both boot-disk-only and full machine)||Image (boot-disk-only)|
|Custom images||Generalized Azure VMs||Custom images|
|VM templates||Resource Manager templates||Instance templates|
|Automatic instance scaling||Azure Autoscale||Compute Engine autoscaler|
|Supported VM import formats||VHD||RAW|
|Deployment locality||Regional (equivalent to Cloud Platform zones)||Zonal|
Mapping high-level terminology for Azure to Google Compute Engine
In provisioning VMs in Compute Engine and Azure, you’ll discover the platforms offer you many of the same features. You’ll be able to:
- Deploy and terminate VM instances on-demand with autoscaling.
- Install a range of available operating systems on your VM.
- Use boot disk images to create VM instances.
- Manage VM instances free of restrictions.
- Tag your VMs for ease of identification.
When it comes to VM access, there are some key differences between Google Cloud vs Azure. These differences depend on the type of machine you are using.
For Linux machines, there are differences in SSH-based machine access. Compute Engine allows you to create an SSH key when you need it, even if your VM instance is already running. The platform also supports SSH from the browser, allowing direct access to your VMs through a web browser, which avoids storing keys on your local machine.
With Azure, there’s no SSH browser access, and you must include your own key if you want SSH-based access.
As for Windows machines, access is similar across the platforms. Both Compute Engine and Azure support access to your VMs through standard channels including Remote Desktop Protocol (RDP) and Windows Remote Management Service.
Both Google and Microsoft offer 100s of machine types, that can be deployed in many different configurations. You can scale your VM resources to meet demand, increasing the number of CPUs and GB of RAM to extreme high-end specifications. These currently top out with:
- Google Compute Engine VMs scaling up to 416 vCPUs and 11,776 GB of RAM.
- Microsoft Azure VMs scaling up to 416 vCPUs and 11,400 GB of RAM.
Both platforms share the same categorization of machine types to help in your resource selection. Depending on your requirements, you can choose machine types from shared core, general purpose, memory-optimized, compute-optimized, storage optimized, GPU, and high-performance categories.
We’ve compiled the following table which lists the up-to-date machine types for both services.
|Machine Type||Azure||Compute Engine|
|Shared Core||N/A||f1-micro – g1-small
e2-micro – e2-medium
|General Purpose||A1 v2 – A8 v2
B1LS – B20MS
D2a v4 – D96a v4
D2as v4 – D96as v4
D2 v3 – D64 v3
D2s v3 – D64s v3
D1-5 v2 – D5 v2
DS1-5 v2 – DS5 v2
|n1-standard-1 – n1-standard-96
n1-highmem-2 – n1-highmem-96
n1-highcpu-2 – n1-highcpu-96
n2-standard-2 – n2-standard-80
n2-highmem-2 – n2-highmem-80
n2-highcpu-2 – n2-highcpu-80
e2-standard-2 – e2-standard-16
e2-highmem-2 – e2-highmem-16
e2-highcpu-2 – e1-highcpu-16
|Memory-optimized||E2 v3 – E64 v 3
E2a v4 – E96 v4
E2as v4 – E96as v4
E2s v3 – E64s v3
D11 v2 – D15 v2
DS11 v2 – DS15 v2
G1 – G5
Gs1 – Gs5
M8ms – M128ms
M208s v2 – M416ms v2
S96 – S576m
|m1-ultramem-40 – m1-ultramem-160
m2-ultramem-208 – m2-ultramem-416
|Compute-optimized||F2s v2 – F72s v2
F1 – F16F1s – F16s
|c2-standard-4 – c2-standard-60|
|Storage-optimized||L8s v2 – L80s v2
L4s – L32s
|GPU||NC6 – NC24
NC6 Promo – NC24r Promo
NC6s v2 – NC24s v2
NC6s v3 – NC24s v3
NV6 Promo – NV24 Promo
NV12s v3 – NV48s v3
ND6s – ND24s
|NVIDIA® Tesla® T4 – NVIDIA® Tesla® K80
NVIDIA® Tesla® T4 Virtual Workstation – NVIDIA® Tesla® P100 Virtual Workstation
|High performance||H8 – H16mH8 Promo – H16mr Promo||N/A|
|Custom VM resource configuration||No||Yes|
Google Cloud and Azure continue to utilize and expand their own network infrastructures, working with partners, to interconnect their globally deployed data centers. They have ambitious expansion plans and offer state-of-the-art networking services to offer high-speed connectivity across virtual machines, other cloud services, and on-premises servers.
In this section, we’ll explore the core networking products offered by Google and Microsoft, as well as a quick look at availability and latency.
|Product||Google Cloud Platform||Microsoft Azure|
|CDN||Google Cloud CDN||Azure CDN|
|Dedicated Interconnection||Cloud InterconnectCDN Interconnect||ExpressRoute|
|DNS||Cloud DNS||Azure DNS|
|Load Balancing||Cloud Load Balancing||Azure Load Balancer|
|Virtual Networks||Virtual Private Cloud||Azure VNet|
|Tiers||Network Service Tiers||N/A|
A comparison of equivalent cloud networking products for Google Cloud vs Azure (Table Source: Google)
Google Cloud and Azure each offer a global network of data centers across multiple regions, countries, and locations. Each provider has distinct availability zones which are great for redundancy, fault tolerance, and low latency. While Azure offers a larger range of regions, Google Cloud has a significantly higher number of locations.
Microsoft Azure network locations are currently available in a broader range of 58 regions and 140 zones.
Both Google and Azure offer a similar Content Delivery Network (CDN) solution, helping you to reduce load times, save bandwidth, and speed responsiveness of your applications, websites, and services.
Named the Google Cloud CDN and Azure CDN, each platform offers deep integration with their native platforms – offering advanced logging and monitoring. As well as a number of security solutions designed to offer resilience against distributed denial of service (DDoS) attacks.
In certain situations, you may find your on-premises-to-cloud VPN doesn’t provide the speed or security needed for certain workloads. In this scenario, you can turn to Azure and Google to lease a high-speed network line with guaranteed capacity. Both platforms offer a range of services:
Carrier peering is a form of dedicated interconnection to the cloud provider through a third-party provider, from which you lease a line. Azure’s offering is ExpressRoute, while Google has Cloud Interconnect.
While each provider offers connection speeds up to 100 Gbps, Express Route has wider choice with102 providers versus Cloud Interconnect’s 24 providers. ExpressRoute also offers a privately leased line, whereas Cloud Interconnect lines use public networks.
Direct Peering is a service currently offered by Google, not Azure. The service allows for a direct connection between your business network and Google’s edge network, without the middleman. Plugging you directly into Google’s services and allowing exchange of high-throughput cloud traffic – available in more than 100 locations and 33 countries across the globe.
Content Delivery Network (CDN) Peering
Google also offers CDN peering. Allowing you to directly connect your resources in the cloud and a CDN provider using Google’s network edge locations. Google supports this for several CDN providers via its CDN Interconnect service. Again – to date – Azure doesn’t offer a competitive CDN peering product. Though it does support dedicated connections to the Akamai and Verizon CDNs within its Azure CDN service.
A DNS service converts your human-readable domain names into the IP addresses that servers use to communicate with each other.
Both Google Cloud and Azure offer managed DNS services that scale in the cloud – known as Azure DNS and Cloud DNS. Almost identical in features, both support most common DNS record types and anycast-based serving. More recently, Google has expanded its feature offering to support DNSSEC, something Azure DNS has yet to adopt.
Google Cloud and Azure each offer load balancing services to help you distribute traffic across multiple instances. All with the aim of improving availability and fault tolerance. Let’s take a high-level look at some of the ways they provide this using different load balancing types:
HTTP(S) Load Balancing
Azure and Google offer layer 7 load balancing, helping you distribute client requests at the application layer to achieve more sophisticated routing than layer 4 load balancing can provide.
TCP/UDP Load Balancing
Both platforms also support layer 4 load balancing, distributing your client requests within a region at the networking transport layer.
SSL Load Balancing
Both providers also support SSL load balancing, offering you encryption and decryption of any data trafficked to or from your services.
You can create isolated and secure virtual networks on both Azure and Google Cloud. Each platform offers you the capabilities to deploy multiple networks which can be further segmented into smaller subnetworks. VMs deployed in these virtual networks will have the capacity to communicate across subnets without further configuration.
The Azure offering is referred to as Azure VNet and is a regional offering. While the Google offering is called Virtual Private Cloud (VPC) and is a global resource. Looking closely at the features and functionality, Google VPC offers some features Azure lacks. Such as shared networking, allowing admins to give multiple projects permission to use a single shared virtual network and its corresponding resources.
The Google Cloud Platform offers Network Service Tiers as part of its product offering, allowing you to optimize your network on performance and price. Google is the first major public cloud provider to introduce a tiered cloud network service offering. To date Microsoft Azure does not offer a comparative option.
Through Google, you can select between a Premium and Standard tier. Opting for the Premium tier gives you access to Google’s high performance, low latency, highly reliable global network. The service routes your traffic through the fastest paths with the fewest hops to speed transport and improve security. You access additional networking services such as global load balancing and you’re protected by a Global SLA.
If you opt for the Standard tier, you’ll connect to a lower performance network which is comparable to other public cloud providers. Your networking services, like load balancing, will be regional and you’ll not have a Global SLA. This a choice for you if cost is a consideration, where you’re willing to sacrifice performance.
To understand the differences this makes to your service, you can regularly check the performance measurements from Cedexis, which compare latency and throughput. As you will see from the graphic below, the Premium tier currently offers almost a 20% decrease in latency against the Standard tier.
Looking at throughput, you will also see the Premium tier offers a 100% increase in throughput versus the Standard tier.
We understand the importance of speed in service. That’s why we here at Kinsta utilize Google Cloud Platform’s premium tier for all of our clients. To ensure lightning-fast load times, minimizing traceroute hops, and decreasing the distance your data has to travel.
Understanding the different storage and disk types your cloud provider utilizes is critically important. These devices will directly impact expected throughput (IO), max IOPs per volume/instance, and the ability to burst capacity for short times – which have a significant influence on performance.
When comparing Google Cloud vs Microsoft Azure storage, we’ll focus on the primary storage options: block storage and object storage.
Block storage is essentially a virtual disk running on a cloud-based virtual machine. Google Cloud delivers block storage utilizing persistent disks – offering SSD and HDD storage – which can attach to instances running on Compute Engine or Google Kubernetes Engine.
Microsoft Azure delivers its block storage solution in the form of page blobs, stored on Azure VHDs, running on an Azure VM.
Apart from the method of data storage, Compute Engine persistent disks and Azure virtual hard disks (VHDs) are very similar. Each offers network-attached disk volumes and the ability to attach local disks should the need arise.
Below is a detailed look at how block storage maps across Compute Engine persistent disks and Azure VHDs:
|Block Storage||Azure VHDs||Compute Engine persistent disks|
|Volume types||Standard Storage (HDD), Premium Storage (SSD)||Standard persistent disk (HDD), SSD persistent disk|
|Management schemes||Unmanaged disks, managed disks||N/A (Google Cloud-managed at the project level)|
|Volume attachment||Can be attached to only one instance at a time||Read-write volumes: Can be attached to only one instance at a time
Read-only volumes: Can be attached to multiple instances
|Maximum volume size||4 TiB||64 TB|
|Disk encryption||Encrypted by default||Encrypted by default|
Table comparing block storage features on Azure VHDs and Google Compute Engine persistent disks
The following table looks at how Compute Engine’s locally attached disks compare to those of Azure:
|Block Storage||Azure||Compute Engine|
|Service name||Local SSD||Local SSD|
|Volume attachment||Tied to instance type||Can be attached to any non-shared-core instance|
|Attached volumes per instance||Varies by instance type||Up to 8|
|Storage capacity||Varies by instance type||375 GB per volume|
Table comparing features of locally-attached disks for Compute Engine and Azure
Distributed Object Storage
Distributed object storage is a way of storing data as objects, also referred to as blobs. Each object comprises of the data itself, an amount of metadata, and a key acting as a unique identifier. Object storage can be implemented at multiple levels including the device-level, system-level, and interface-level.
The distributed object storage offering from Azure is called Azure Blob Storage, and Google Cloud offers Cloud Storage. They are similar in many ways, using unique keys to identify objects, and support metadata information that includes object size, date of last modification, and media type. They both support the functionality to edit and add custom metadata fields and are most commonly used for data types including static web content and media.
Each platform supports additional features including object encryption, replication, versioning, lifecycle management, and change notifications. Along with an uptime service level agreement (SLA) and policies in place to credit you should they not meet these requirements. You can find their policies and guarantees in the Azure Storage SLA and the Cloud Storage SLA.
Of course, there are also differences in how the services are delivered. With the table below outlining a high-level look at the comparative features and terminology for Azure Blob Storage and Google Cloud Storage:
|Feature||Azure Blob Storage||Cloud Storage|
|Unit of deployment||Container||Bucket|
|Deployment identifier||Account-level unique key||Globally unique key|
|File system emulation||Limited||Limited|
|Object types||Block blobs, append blobs, page blobs||Objects|
|Object versioning||Manual, per-object snapshotting||Automatic versioning of all objects in a bucket (must be enabled)|
|Object lifecycle management||Yes (through lifecycle rules or Azure Automation)||Yes (native)|
|Object change notifications||Yes (through Azure Event Grids)||Yes (through Pub/Sub)|
|Service classes||Redundancy levels: LRS, ZRS, GRS, RA-GRSTiers: Hot, Cool, Archive||Standard, Nearline, Coldline, Archive|
|Deployment locality||Zonal and regional||Regional and multi-regional|
Table comparing features of object storage is Azure Blob Storage and Google Cloud Storage
When we talk about cloud security, we are focusing on the underlying technologies, controls, processes, and policies which combine to protect your cloud-based systems, data, and infrastructure.
Microsoft and Google are renowned for a deep commitment to providing the highest levels of cloud security. With each provider continuing to evolve a security model built on a development history spanning more than a decade.
At a high level, they deliver cloud security in three ways:
- Security of the cloud platform – delivering security capabilities that are built into the infrastructure of the cloud platform, providing protection by default.
- Security in the cloud platform – delivering security products and services within the platform that can be configured to protect your applications and data.
- Security anywhere – expanding security capabilities beyond the cloud platform to protect your assets regardless of location.
In this section, we will compare some of the key features of Google Cloud security vs Azure security.
With the continuing rise in regulatory control of information by both governments and industry, compliance of your cloud platform is critical. Both Google and Azure implement stringent security policies and processes ensuring they meet some of the toughest compliance requirements including CSA STAR, GDPR, HIPPA, PCI-DSS, and a range of ISO standards.
Encryption of your data is a critical requirement, regardless of whether it’s in the cloud. Encoding the data ensures that – should it be intercepted – it is almost impossible to decipher without a decryption key.
Within their cloud infrastructure, Azure and Google Cloud support encryption as default using 256-bit AES. They also offer you the ability to control your own encryption keys and deliver encryption at rest and in transit. Google refers to its service as the Cloud Key Management Service, while Microsoft refers to its Azure service as Key Vault
Firewalls provide the first line of network defense for any infrastructure. Both Google Cloud and Azure provide state-of-the-art firewalls, offering you configuration capabilities through firewall rules so you can control who has access to the network.
At Kinsta, we understand the importance of security. It’s built into our architecture from the ground up, using the Google Cloud platform to deliver secure WordPress hosting for all our clients. In addition, Kinsta delivers another security layer completely isolating each account and WordPress site using Linux containers (LXC), and LXD to orchestrate them.
Identity Access Management (IAM)
An Identity Access Management system will give you control over who can access your system, stopping unwanted visitors at the front door.
Both providers offer an in-built IAM system, Google has Cloud Identity and Access Management (IAM) and Microsoft has Azure Active Directory. They combine a similar range of features and functionality that include user roles, access policies, and multi-factor authentication.
Delivering control over who has access to your applications and data, what they can access, and what they can do to your data.
Security in the cloud is a shared responsibility. A key factor in maintaining your cloud security is in understanding the division between which security tasks remain with you, and which are handled by the provider.
Both Azure and Google Cloud Platform have clear shared responsibility models which help you understand who does what. Below you can see a visual depiction of the shared responsibilities for each provider:
Google Cloud Platform
Google and Microsoft invest heavily in the continued employment and expansion of their security departments. With each provider working to attract and retain the very best talent in the cybersecurity sector, ensuring the continued evolution and improvement of their cloud security services.
In terms of numbers, Microsoft has an edge employing more than 3500 cybersecurity experts, versus Google’s 550 cybersecurity experts. Both providers also actively tap the expertise of the wider cybersecurity market through their respective Azure and Google Vulnerability Reward Programs. Offering financial rewards upwards of $100,000 for any uncovered security weaknesses.
Support and Uptime
When deploying a cloud service, you may run into situations where you need additional guidance and support. Both Google Cloud and Azure offer extensive documentation to educate you on technical specifications. Along with guidance on how to configure, deploy, and maintain their range of cloud services.
In addition to this, both providers also offer community support platforms that are home to a vast network of cloud users and experts. These forums have topics that span tutorials, discussions, and meetups.
Below are links to the respective documentation and community support portals:
- Google Cloud Documentation
- Google Cloud Community Support
- Azure Documentation
- Azure Community Support
Eventually, you’ll run into a situation where you need more in-depth expert guidance of an immediate nature. In this situation, it’s better to have an official support solution in place, direct from the cloud provider.
Both Azure and Google Cloud have cloud support plans available. Make sure you read and understand the plans and associated fees to ensure you get the service you need, at a price you can afford.
Google Cloud Support Plans
- Google Cloud offers support plans in two types – role-based support and premium support.
- Role-based support has three tiers – Basic, Development, and Production which range from free to $250/month per user.
- Each tier increase offers additional support types, faster response times, more communication channels, increased availability, and options for escalation of issues.
- It’s possible to combine Development and Production role-based support plans.
- Premium support is the highest level of support with a price tag that can be upwards of $150,000 per year and includes an additional cost at 4% of GCP/G-Suite spend depending on the services utilized.
- Premium support offers rapid 15 minute response times, a dedicated account manager, training, new product previews, and more.
- Support is fully customizable – you can estimate your costs using the Google Cloud Platform Pricing Calculator.
- Google Cloud also offers legacy support options which span Bronze, Silver, Gold, and Platinum support plans – soon to be retired fully.
Azure Support Plans
- There are 5 Azure support plans available – Basic, Developer, Standard, Professional Direct, and Premier.
- Basic, Developer and Standard support plans are directly comparable to the Google Cloud role-based support plans with cheaper prices ranging from free to $100/month per user.
- Each level increase adds additional layers of support including more support types, more communication channels, faster response times, and general architecture support.
- Professional Direct support positions itself between the role-based and Premier support, with a price tag of $1000/month per user.
- It’s aimed at businesses that have a business-critical dependence on Azure.
- Support is a step above Standard – with response times under 1 hour, architecture support, operations support, training, and a dedicated account manager.
- Premier support is the highest level of support – you’ll need to contact Microsoft for prices.
- It’s aimed at businesses with dependence on Azure across multiple products.
- Support offers response times of 15 minutes, customizable architecture and operational support, on-demand training, a designated Technical Account Manager, and launch support.
First-class expert support is critical for any service.
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Maintaining the uptime of your website and services is critical to your business. Any outages will have a negative impact on the productivity of your business, with staff unable to access key systems and customers unable to make purchases through your website.
To keep track of the service status – critical in an outage – you can check each cloud providers current performance through the following dashboards:
If you’re interested in tracking past incidents, including their causes and duration, both providers offer an incident status history:
That being said, both providers have exemplary performance and so the likelihood of outages is minimal. With the global presence of Google Cloud and Azure networks across 100s of regions and locations, both providers offer a robust failover option even in the event of widespread outages.
Billing and Pricing
Pricing is one of the most difficult comparison aspects when looking at cloud providers. There are so many variables, with every provider offering a unique approach to pricing and billing.
Below are just a few variables that will influence your cloud costs, making direct comparisons between providers a real challenge:
- Virtual Machines – number of instances, number of CPUs, GB of Ram required, operating system.
- Storage Disks – type of data, size of storage, redundancy requirements.
- Subscription model – purchasing by the second, minute, hour, day, month, or year.
- Payment model – opting for pay-as-you-go, reserved instances or a long-term contract mode.
- Location – where your data center is located.
To further complicate the challenge, many cloud providers don’t have a straightforward way of calculating costs. Google Cloud and Azure are no exception.
To help, we’re going to provide you with some tools, information, and guidance so you can get started with your own personalized Google Cloud vs Azure pricing comparison.
Google Cloud vs Azure Pricing Comparison
As you will see from the Google Cloud and Azure product pages, there are 100s of different services to choose from. With each product having its own overview and pricing sections, you can quickly lose track of potential costs. Even when pairing just a few compute and storage resources.
Thankfully, both providers offer a pricing calculator. So, provided you know the cloud resources you require, you can take the first step in building a comparable pricing estimate:
There are also a number of free comparison tools available on the web that can give you a high-level look at costs. Cloudarado is one such tool, where inputting some basic cloud resource requirements will begin to provide you with some ballpark comparisons of costs.
As an example, we chose a single VM instance running a Linux OS, powered by 16CPUs and 32 GB RAM, and 2TB of storage. This gave an immediate cost estimate which is outlined below:
|Cloud Provider||Cloud Hosting Offer||Price Per Month|
|Google Cloud||Custom Machine 32 GB RAM / 16x CPUs2 TB disk||$ 421|
|Microsoft Azure||D16 v3 Machine 64 GB RAM / 16x vCPUs400 GB + 1.61 TB disk||$ 627|
Whilst these free comparison tools can be helpful to get a quick cost estimate, you’ll need to dive into the detail with the Google Cloud and Azure calculators to get an accurate understanding of your potential costs.
So, let’s dive a little deeper and look more closely at a pricing comparison for the platforms. We’ll focus specifically on the compute costs of Google Compute Engine and Azure VMs – as compute resources typically amount to two-thirds of total cloud spend. They also form the foundation for most other services.
Assumptions for Cloud Pricing Comparison
For an apples to apples comparison, we’ve kept the same region, CPUs, and operating system for Azure VMs and Compute Engine:
- Region: US East- North Virginia (Google – us-east4, Azure – east-us).
- Operating System: Linux – Free (CentOS).
- vCPUs/Cores: 4.
We’ve chosen instances with comparable RAM and 4 CPUs, across the instances/VM types:
- General purpose.
- GPU instances/VMs.
Below is a table containing the chosen instances for the comparison:
|Instance Type||Azure VM||Azure RAM
|Compute Engine||Google RAM
|Memory Optimized||E4 v3||16||n1-highmem-4||26|
|GPU||NC6||56||NVIDIA® Tesla® T4||64|
Both Google Cloud and Azure offer pay-as-you-go models. While this type of pricing model gives you flexibility to control spending, it comes at a cost, with pay-as-you-go being the most expensive pricing per hour.
|Instance Type||Azure VM||Azure Price
|Compute Engine||Google Price
|Memory Optimized||E4 v3||$0.252||n1-highmem-4||$0.166|
|GPU||NC6||$0.9||NVIDIA® Tesla® T4||$1.40|
Table showing pay-as-you-go hourly rates of Compute Engine vs Azure
As you can see from the table above, Google Compute Engine has the lowest price for General Purpose, Compute Optimized, and Memory Optimized machine types when compared with its Azure counterparts.
This is due to differences in billing methods. Azure only offers a flat rate for pay-as-you-go instances, Google applies Sustained Usage Discounts which are automatically added once you pass a certain threshold. This discount amount scales up, the more you use the services, with savings starting at 15% and ramping up to 60%. Without this discounting method, Google Compute Engine would actually be more expensive per hour.
Interestingly, Google Cloud also offers an even higher discount with Preemptible Virtual Machines. If you’re open to Compute Engine terminating your instances in the event they are needed for alternative resources, you can make an even greater cost saving. A quick look at the n1-standard-4 processor, showed a 75% price drop from $0.15/hour to $0.04/hour if you opted for a preemptible machine type. It’s important to note preemptible machine types are only available as part of Google Cloud’s pay-as-you-model.
Looking at GPU instances, Azure has the edge here with a significantly lower GPU price thanks to its native processors. Google Cloud utilizes the third-party NVIDIA platform to deliver its GPU offering, significantly increasing the price point, even when Sustained Usage discounts are applied.
Committed Use Discounts vs Reserved Instances
If you’re serious about your cloud deployment and willing to make a long term commitment upfront, you can make significant savings over a pay-as-you-go model. Both Google Cloud and Azure support long-term pricing models, offering to reward upfront commitments of 1 year or 3 years.
Google Cloud’s long-term subscription model, referred to as Committed Use, promises savings of up to 75%. While the Azure equivalent of Reserved Instances, promises equally impressive savings of up to 80%.
As with all things cloud, there are a number of variables that will influence the level of discount you receive. A quick exploration of the pricing calculators will reveal that instance types, location, and operating system are just a few of the variables that will influence savings. There are doubtless many more, so be diligent in digging out and applying those variables.
With that in mind, let’s now compare how a 1-year commitment through Committed Use and Reserved Instances has influenced the price comparison between the two cloud giants.
|Instance Type||Azure VM||Azure Price
|Compute Engine||Google Price
|Memory Optimized||E4 v3||$0.1564||n1-highmem-4||$0.1594|
|GPU||NC6||$0.5733||NVIDIA® Tesla® T4||$0.88|
Table showing hourly rates for 1 year Committed Use of Compute Engine vs 1 year Reserved Instance of Azure
Surprisingly, with Azure offering discounts up to 40% for a 1-year Reserved Instance, the balance has shifted. Azure VMs have become a cheaper option across all four categories of General Purpose, Compute Optimized, Memory Optimized, and GPU machine types. In this scenario, Google Compute Engine was revealed to be up to 30% more expensive.
To complete the comparison, let’s see if a 3-year commitment through Committed Use and Reserved Instances has any further effect on the price comparison between these platforms:
|Instance Type||Azure VM||Azure Price
|Compute Engine||Google Price
|Memory Optimized||E4 v3||$0.1||n1-highmem-4||$0.1239|
|GPU||NC6||$0.3995||NVIDIA® Tesla® T4||$0.64|
Table showing hourly rates for 3-year Committed Use of Compute Engine vs 3-year Reserved Instance of Azure (as of January 2020)
By committing to a 3-year reserved instance, there has been no change over the 1-year commitment as to which provider is cheaper. Azure continues to offer higher discount levels of up 62%, versus Google’s 39%, against its equivalent pay-as-you-go model, ensuring Compute Engine remains more expensive across all four categories of General Purpose, Compute Optimized, Memory Optimized, and GPU machine types.
In this 3-year commitment scenario, Google’s machine types were up to 46% more expensive than their Azure counterparts.
In the event you’re just starting out, not ready to commit, or don’t need significant resources, both cloud providers offer a free tier with trials across a range of their products and services. The Google Cloud Platform Free Tier is comprised of two components:
- A 12-month free trial with access to any Google Cloud services and $300 of credit, which must be spent within the 12-month trial
- Access to common Google Cloud resources that are always free of charge, with a limited usage policy
Unsurprisingly, there is a range of eligibility requirements for the free tier, such as not having been a paying customer or having previously completed a free trial.
If you qualify, you will gain ‘always free’ access to 18 core Google Cloud products which span compute, database, storage, data analytics, management & developer tools, AI & machine learning and security services.
Below are some of the key products along with their service restrictions:
- 1 F1-micro VM instance with a 30GB HDD per month – only available in the US region.
- 5 GB of cloud storage – with 5,000 Class A Operations and 50,000 Class B Operations per month.
- 1 NoSQL document database with 1 GB storage – 50,000 reads, 20,000 writes, 20,000 deletes per day.
- 28 instance hours a day of App Engine.
The Azure Free Trial adopts a similar approach with two components, there are however some key differences:
- A 12-month free trial of certain Azure services with limited usage and $200 of credit – which must be spent in the first 30 days.
- Access to common Azure resources that are always free of charge, also subject to a limited usage policy.
Like Google Cloud, there are a number of eligibility restrictions that you must meet before you can qualify for the free tier.
If you qualify for the Azure free account, unlike Google Cloud where you can trial any service for 12 months, you’ll only gain access to 20 Azure services. These include key products like Linux and Windows VMs, Managed Disks, File and Blob Storage, and SQL Databases. These services will come with limited usage which you can expand with the $200 of free credit.
You’ll also unlock forever free access to a wider 25+ Azure products which include compute, databases, networking, identity, security, developer tools, analytics, management & governance, AI & machine learning, and container services.
Below are a few of those core products:
- Azure App Service for 10 web, mobile, or API apps with 1 GB storage.
- Azure Active Directory for identity management – supporting single sign-on (SSO) for 10 apps per user.
- 5 free users on Azure DevOps.
- Free access to DevTest Labs to create quick, simple, and lean app testing environments.
When it comes to the free tier, Google Cloud has the edge over Azure in the long run. Google Cloud offers the key elements of a cloud deployment foundation – VM instances and storage – as part of its ‘always free’ offering. While Azure offers VM instances and storage initially, these services expire after 12 months.
Is Google Cloud Cheaper than Azure?
Even after researching multiple products, services, and pricing models of each cloud provider, there is no definitive answer as to whether Google Cloud is cheaper than Azure.
The real answer is, it depends. It depends on so many variables we’ve touched on in this article. Which product are you looking at, the resource requirements of that product, which data center you’ll run the service from, whether you’re willing to commit upfront to long-term services, and many more subtle elements we’ve yet to even uncover.
You’ve already seen in our Google Cloud vs Azure compute services pricing comparison how changeable the pricing structure can be. In a pay-as-you-go model, VM instances in Google Compute Engine can be configured to unlock discounts which make it 75% cheaper than running Azure VMs.
And yet, shifting to an upfront commitment of 3 years will see the pricing pendulum swing and Azure VMs becoming up to 30% cheaper than Compute Engine instances.
Ultimately, the answer to whether Google Cloud is cheaper than Azure relies on you. The unique cloud requirements of your business will define which cloud provider is the cheapest option for your business. But, I’ll also leave you with a final question, does cheaper mean that it’s better?
In comparing these two cloud giants, we’ve been seeking the same answer that many quests for: which is better Google Cloud or Azure?
Having completed an extensive exploration and compiled our research, the honest answer is we still don’t know. Both providers offer an incredible range of high-quality products and services, each with a long list of pros which far outweigh the cons.
Here at Kinsta, we are partial to Google Cloud. Which is why we use it to power our WordPress hosting solutions. Google Cloud continues to improve its state-of-the-art platform. Growing and evolving its offerings while planning new data center locations for the year ahead.
Google’s accelerating popularity and success is reflected by the doubling of its annual cloud revenue run-rate, reducing both Azure market share along with AWS market share. If you care about speed and pricing, the Google Cloud Platform is definitely one you want to check out.
Azure has also made great strides in recent years. A result of Microsoft CEO, Satya Nadella, shifting the company to a ‘cloud first’, ‘mobile first’ strategy. Like Google, Microsoft continues impressive data center expansion plans and is heavily investing in improving its network infrastructure.
Azure’s compliance, redundancy, and availability capabilities make it a hugely appealing platform. With the platform also seeing impressive growth of 60% over the past year, likely set to continue.
But we’re still only scratching the surface. Taking a wider perspective, the constant competition between leading cloud providers can only be a good thing. As they seek to gain market share from each other, we’ll reap the benefits of new and improved products and services, wider availability, and lower prices. Long may it continue.
Perhaps there is one cloud computing provider you prefer over another? Tell us your thoughts and reasons in the comments below.
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