Comparison Overview with NIX: Azure vs. GCP vs. AWS

Cloud computing is at the forefront of today’s all-consuming digitization, seeping into all sorts of industries with advanced energy-efficient remote cloud opportunities. It didn’t take long for fierce competition to establish in the niche through the powers of leading storage tech providers. And as much as the competition has been shifting through the years, today we have three common cloud computing favorites – Microsoft, Google, and Amazon with their respective cloud-based storage platforms – Azure, Google Cloud Platform (GCP), and Amazon Web Services (AWS).

These particular platforms dominate the IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) market niches. So we decided to compare each fair and square to help you see which fits your particular goals and specifics best. Here’s the ultimate AWS vs. Azure vs. GCP comparison.

GCP vs. AWS vs. AZURE: Market Share Overview

While these top three leading platforms share dominance over the cloud computing market in general, they have firmly occupied their fair positions according to the market share and total rates of popularity. Different sets of features, tools and capacities fit different users from different regions, etc., forming a clear segmentation. 

AWS

Amazon’s cloud capacities represented through the AWS platform confidently lead the competition. The report by Synergy Research Group says that AWS currently holds a 33% total share of the global cloud market, covering the needs of businesses of all scales alike. The in-depth versatility of the platform is achieved due to the exponential system scaling capacities, which makes it a top-performance powerhouse of a cloud platform.

Azure

The same report indicates Microsoft’s 18% of the total share in the same niche, placing it at the second position with the underlying characteristics that best fit enterprises. Especially those with their own operating data centers and enterprise data warehouse solutions, with which Azure can be well integrated due to its hybrid and private cloud capabilities.

GCP

According to the underlying report, around 5% of the market is covered by Google’s platform. And this state of things more than pleases the Google guys in terms of their work agenda and the industry pace at which they are moving. The mighty company seems to be seeping into the cloud niche very gradually and carefully, targeting the widest user segments at the moment.

AWS vs. Azure vs. GCP: Gains and Losses

With their firm general positions in the market, each platform has more to it than the overall success on the superficial level. Going a bit deeper into the GCP vs. AWS vs. Azure analysis, there are particular pros and cons every solution can be characterized with. Let’s take a look. 

AWS Pluses and Minuses

Pluses:

• Vast technical capacities – Amazon Web Services is a platform that encompasses an enormous area of cloud-based operations, providing easily scalable cloud space with the expansion potential limited only by the specific needs and vision of the client.
• Flexible features – services, tools, and other capabilities provided by the huge AWS platform are numerous, tackling tasks from daily management routine to in-depth data analytics and smart predictions.
• Stable data transfer – AWS helps efficiently avoid data loss during storage or server data transfer, getting tons of connected risks out of the way.
• High data availability – AWS users may choose data storage options that are most close to their geographical location to avoid storage distance.

Minuses:

• Focus on public cloud – enterprise-oriented capacities are somewhat limited here in lieu of private and hybrid cloud opportunities available out-of-the-box, making AWS an option to be carefully considered for internal corporate use.
• Somewhat confusing costs – one of the common complaints among companies that prefer AWS is a non-clear long-term pricing policy with shifting conditions and unclear conditions for further budget strategizing.

Azure Pluses and Minuses

Pluses:

• The power of Microsoft – the giant cloud vendor basically takes all its on-premise gist (including software solutions like .NET, SQL Server, Office, etc.) and adjusts it for convenient cloud-based use, giving clients the best stuff Microsoft has to offer.
• Widespread ecosystem – we can say confidently that a majority of companies are using some Microsoft software solutions here or there, and being readily integratable with all of them, Azure comes in as a widely flexible option.
• Enterprise performance – Azure is a great solution for most enterprises out there, allowing to achieve custom cloud infrastructures built on the well-tried-and-tested powers of mighty Microsoft.

Minuses:

• Third-party integrations – yes, Microsoft is readily integrated with solutions of a similar nature; however, one may experience significant issues when integrating with non-Microsoft products.
• Limited flexibility – expanding the above point, Azure can help achieve a sturdy enterprise system if the workflow is mostly Microsoft-based, but the overall platform versatility is hindered by an inability to completely freely customize the cloud infrastructure inside and outside.

GCP Pluses and Minuses

Pluses:

• The Kubernetes standard – in-depth containerization helps GCP handle big data analytics and ML-powered data processing for faster and smarter field operation results.
• Load balancing and scaling – Google is a very savvy provider with smoothly running data centers and rapidly responding services as a whole.
• Google ecosystem – all sorts of software solutions created by Google are also very commonly used by companies seeking cloud opportunities, which makes the gradual adoption of GCP a performance-reinforcing piece of cake of an effort.
• Open-source opportunities – as always, Google enables lots of free customization space for all open-source enthusiasts out there, forming a whole community of eager freethinking GCP users.

Minuses:

• Not enough corporate agenda – the area of application of GCP is narrowed down due to the system’s more novel, startup-oriented nature, with the infrastructure providing some market-defining cloud tools that cannot really serve all-in-one corporate cloud purposes.
• Tech limitations – the App Engine provided by GCP supports only PHP, Java, and Google Go, restricting the overall range of compatible software approaches and solutions.
• Costly fees – working with GCP, it comes in somewhat expensive to manage data downloads and cover support expenses (with the average monthly support fee being $150).

The AWS vs. Azure vs. GCP stand results:

1. AWS is by far the most high-performance and flexible complex cloud software solution out there, which is, however, priced accordingly and requires proper skills;
2. Azure can make a reliable enterprise cloud computing foundation, working on proven Microsoft solutions in its core which, however, have some proven flaws, too;
3. GCP may not be as vast out-of-the-box, but the open-source, authentically flexible software nature allows achieving practically the same results.

Amazon AWS vs. Azure vs. Google Cloud: Services Comparison

This cloud web services comparison wouldn’t be complete without enlisting essential services each platform offers. Going even deeper than that, we should consider specific capacities and services that define each platform. 

Computing Power

AWS

In the heart of AWS system performance, powers lie the Elastic Computer Cloud (a virtual machine management service) and container services that can be easily integrated. Elastic Computer Cloud is the core web service that enables an autonomously scalable high-performance cloud computing environment. 

On top of that, container services such as Kubernetes or Docker can be used to automate cluster and server management workload. Meanwhile, other services like Beanstalk, Lightsail, Batch, etc., expand the cloud environment capabilities further. 

Azure

Microsoft’s solution relies on Virtual Machines and a bunch of sturdily connected services. Virtual Machines make up the core system of the platform, providing high-level security, hybrid cloud capacities, extensive support of other Microsoft services, and a voluminous catalog of instances for boosting overall performance rates. 

AI- and ML-powered features are also present here. Virtual Machine Scale Sets is the system that takes care of auto-scaling while Kubernetes-based systems handle containerization. There is also a Batch service and Cloud Services that come as a great alternative to Beanstalk.

GCP

The powerhouse of Google’s platform is called Compute Engine and it can help you automate discounts, work with predefined and custom machine types, employ per-second billing, and optimize data center energy-consumption rates by organizing carbon-neutral infrastructure and cutting energy expenses in half.

Even though GCP isn’t as extensive in its capabilities as the above two platforms, it comes in with inherited Kubernetes powers that help set all microservices and containers specific in place from container deployment to all the other management.

Storage

AWS

Amazon offers a solution called Simple Storage Service (S3) to store data, which is a highly-scalable, well-established system with a great passionate community of savvy specialists. The storage capacities are, basically, unlimited and scale along with your resource-consumption needs. And you may as well upload up to 5 GB in one go if you need to handle some huge or batch files. 

Azure

Microsoft’s storing solution is called Blob Storage, and it is a versatile system that handles unstructured data with inherited capacities. It is great in that it can be easily integrated with a bunch of additional applications, and you can upload up to 5 TB at once.

GCP

Google Cloud Storage is a completely original data-storing platform that offers extensive integration capabilities, firm data uploading consistency, and resumable uploads as a bonus tool. The storage is well optimized for handling unstructured data and allows an immediate upload of files weighing up to 5 TB. 

Data Analytics

AWS

When it comes to insightful data analysis tools, AWS offers: 

• Elastic MapReduce for data processing;
• Data Pipeline for convenient data orchestration;
• Kinesis Streams for real-time data streaming;
• Kinesis Firehose for large-scale data ingestion;
• Quick Sight for gaining in-depth insights during data analysis.

Azure

Azure doesn’t lag behind too far, offering an original Azure Synapse Analytics service for integrating, warehousing, and analyzing data while there are also such tools as:

• HDInsight;
• Power BI;
• Azure Machine Learning;
• Azure Cognitive Services;
• Azure Data Factory, etc.

GCP

Google’s platform employs yet another unique solution for data analytics purposes called BigQuery – a fully managed enterprise data warehouse that makes querying and storing huge datasets easy, including with the help of tools like:

• Cloud Data Fusion;
• Cloud Dataflow;
• Cloud BigTable;
• Cloud Dataprep, etc.

Regional Availability

AWS

Amazon Web Service covers 25 geographic regions with 81 availability zones. 218+ edge locations, and 12 Regional Edge Caches.

Azure

Microsoft Azure runs 60+ regions with a minimum of three availability zones in each region with more than 116 edge locations (Points of Presence).

GCP

Google Cloud Platform has 27 cloud regions with 82 zones and 146 edge locations.

There are also Government Cloud solutions offered by every provider for specialized governmental utilities.

Pricing

AWS

The problem with calculating the potential cost of employing AWS is that there are so many variables, it’s easy to lose track and see many unexpected costs spawn here and there. This is why specialists usually use specialized cost management tools here. Essentially, you can pick to be billed in three different ways – a) based on resource-consumption rates, b) based on a Reserved Instance pricing model, c) per hour of use. 

Azure

You literally pay for every second of using the storage – no more, no less – and you pay for it on a per-minute basis. Bills are also rounded up every minute. Still, you should employ the assistance of proper specialists to count costs here as well, as licensing options may confuse you while there are also situation-based discounts that may help optimize overall pricing.

GCP

Similarly to Azure, GCP bills you per minute, yet it rounds up bills every 10 minutes. And as far as it goes, this is the most cost-friendly solution out there that keeps its pricing in line with the capacities it offers. 

The AWS vs. GCP vs. Azure pricing results:

• AWS has an intricate cost formation system and is definitely not cheap;
• Azure’s pricing is transparent out-of-the-box, but once add-ins come into play, hidden costs arise;
• GCP is transparent and flexible in pricing, which only reflects its open-source nature.

AWS, Azure, and GCP: Big Choosing Dilemma

It is time for the GCP vs Azure vs AWS showdown.

AWS streamlines extensive scalability, helping avoid and eliminate tons of common risks, pitfalls, and unnecessary efforts in the process. It is flexible when it comes to cost management and smoothly integrates with third-party services. Yet it is a system that requires profiled specialists to run properly, sets a felt price for resources used, and provides enterprise features only as an extra purchased bonus. 

Microsoft Azure is user-friendly, simple, and extensive out-of-the-box. It can be easily reinforced with a whole arsenal of integratable MS services and tools (extra advantage for Windows-powered offices out there). It also may fit a company of any scale and help achieve reasonable cost-efficiency. However, with this one, you should really watch your data transfer intensity to avoid extra costs and, in the long run, it may not fit your needs if you are a large enterprise that needs a large all-in-one solution if you don’t put enough tailored effort into configuring and managing it.

GCP comes in with in-depth data storage and analytics powers, seamless integration with plenty of other Google services, and reasonable, flexible pricing models. The confines of the Google ecosystem, however, may also be considered a tech limit while the choice of programming languages to use is also quite restricted, and there are regional limitations as well. 

Amazon AWS vs. Azure vs. Google Cloud bottom line:

• AWS for medium- to large-scale enterprises requiring a versatile all-in-one solution with a lot of customization and expansion freedom;
• Azure for small- to large-scale companies requiring a powerful all-in-one system reinforced by a sturdy Microsoft ecosystem;
• GCP for small-scale companies or separate goals and needs that require cost-efficient yet powerful smart tools, cloud optimization features, and more.

Consider NIX United Your Trusted Partner

NIX United is a seasoned provider of cloud capacities in terms of services from basic cloud deployment to in-depth optimization, integration, and analysis. We can set a team tailored to your project individually to take on whatever tasks you have on the agenda.

We deliver our profiled technical expertise through tailored custom software development services that help businesses and startups scale reasonably in accordance with goals and capacities. From regular CRM integration to custom cloud hardcoding efforts – we do it all. And we’ll also help you decide the best fit out of Azure vs. AWS vs. GCP for you.

Final Thoughts

Yes, Amazon Web Services is a leading powerhouse cloud platform with the computing strength accumulated via extensive solutions for pretty much all scales of business. But the power of two of its competing platforms is their ability to fill in the “big brother’s” gaps and expand to specifically required capacities. The fact that they are right now tackling such an industry giant makes them serious competitors already. 

So keep your eyes open and focus on what fits you individually rather than on universally accepted best solutions. Meanwhile, we hope that this comparison of AWS, Azure, and Google Cloud gives you a clearer idea of which direction to settle with.

FAQ

01/

Which is Better: AWS, GCP, or Azure?

The ultimate answer to the question of cloud Amazon vs. Google vs. Microsoft should be given after thorough research and analysis of all the pros and cons to identify the option that fits your specific needs and goals best. In our comparison article, for instance, you may learn that GCP may as well be adjusted to fit your needs better than AWS, which is a universally powerful solution that may have things you don’t need.

02/

Which is Cheaper: Azure, AWS, or GCP?

GCP is the cheapest option and it lacks in terms of features accordingly. If we compare Microsoft Azure vs Google Cloud vs AWS in this aspect, then AWS is the most cost-intensive, then goes Azure, and GCP at the last position as the most affordable option. However, long-term costs may be optimized in a variety of ways when working with either platform.

03/

AWS vs. GCP vs. Azure: Which one is More Secure?

Again, the final choice of Microsoft Azure vs. Amazon AWS vs. Google Cloud should be considered based on individual needs, requirements, and capacities. Thus, if you have a savvy team of cybersecurity specialists by your side, you may as well turn GCP into a firmly protected cloud. This is the dilemma of the AWS vs. GCP vs. Azure stand that reliable consultants can help you clarify and handle.