In a previous blog post, we ran through Azure’s features and compared and contrasted Azure to Amazon’s cloud offering, AWS. In this blog, we continue with this theme and compare the Google Cloud Platform (GCP) with Microsoft Azure.
The Google Cloud Platform journeyed into the mainstream back in 2011, so it’s been around as long as Microsoft Azure. Its initial use was for Google’s backend services like YouTube and the Google search engine. These backend services were ultimately shared with enterprise, and it’s grown as a platform ever since.
To make the comparison easier, we’ll use the same structure as the previous blog post, and after you’ve read this final comparison, you’ll have a better understanding of the Azure, AWS, and the GCP landscape!
Computing, Storage, and Databases
Just like Azure, the GCP offers services to handle all your computing, storage, and database needs; these services let you crunch, store, and query data at scale. Let’s explore these three pillars of Azure and the Google Cloud platform and see how they compare.
The core feature of both platforms, Azure has the concept of Virtual Machines (or VMs), whereas the Google Cloud Platform offers the Google Compute Engine (GCE) which effectively performs the same functions as an Azure VM.
The GCP and Azure both do well in this category, and it’s not surprising as it’s a core component of any cloud computing platform. They both have similar on-demand pricing models that charge by the minute, and regarding discount pricing, they operate in very different ways.
To widen the market grip, Microsoft offers substantial VM discounts through its Enterprise Arrangements (EA) if businesses commit to company-wide installations of Microsoft Servers – something to consider if you’re happy to adopt a Microsoft-wide implementation.
Both support Windows and *NIX images, so you’re good on that front, and as you’d expect, you can provision servers to your unique RAM, SDD requirements and so on.
The Google Cloud Platforms storage mechanism has a few services to handle storage, Google Cloud Storage, and Google App Engine Persistence Disks. Microsoft Azure’s is called Blob Storage – both GCP and Azure do well in these categories, and you’d be hard pushed to decide on a winner.
Having a database in the cloud is typically needed for most modern applications, and the GCP and Azure both let you easily provision these services. Both Azure and the GCP offer relational databases or NoSQL databases. Azure’s offering for relational databases is the tried-and-tested SQL Server, and with NoSQL, Azure’s flagship product is called DocumentDB, with a low-cost key/value store called Table Storage.
The GCP relational database service is called CloudSQL and is a managed MySQL database whereas the GCP NoSQL offerings are called Cloud Datastore and BigTable. BigTable drives much of Google’s products and services and can also integrate with Hadoop.
Picking a winner this category is difficult as there are indeed many services to choose from, but one notable point that might tip this category in Azure’s favour is out-of-the-box support for cross-regional database geo-replication.
We don’t need to repeat too much from the last blog post, but for developers using tools such as Microsoft Visual Studio (VS), the integration with Azure is hard to beat. Visual Studio will even automatically provision services for you and create accounts, all from the VS IDE.
The Google Cloud Platform features a set of Client API libraries, one of which is .NET. This allows developers that are familiar with Microsoft technologies to consume and integrate services hosted in the Google Cloud and programmatically run them using a .NET coding language such as C#. The Google Client API library can also be added to a Visual Studio Project as NuGet package so downloading and installing it is straightforward.
To publish to Google Cloud, developers can install Google Cloud Tools for VS which makes deploying .NET projects a bit easier for you, that said, consuming and integrating services in Azure via Microsoft Visual Studio is just a smoother experience in general.
Machine Learning and Artificial Intelligence
Machine learning and advancements in artificial intelligence have been growing at rapid rates, so Google and Microsoft have recognised the demand for products and services that empower software firms and businesses with the ability to effectively take machine learning algorithms “off the shelf”. It is often in the form of a REST API endpoint and easily integrates with their existing tech stack.
Just some of the areas in which cognitive intelligence can be added, include, but are not limited to:
- Vision and Image Recognition
- Text Classification
Just like Azure, Google Cloud offers its own set of machine learning services and tooling, which to be fair, can do pretty much everything that Azure can.
There are a few exceptions, however. At the time of this writing, the Google Video Analysis APIs don’t support Activity Detection, Facial Recognition and so on, whereas AI video recognition services that ship with Azure are more comprehensive. Other areas where the GCP AI services fall short of the mark are with processing speech and text. This is something to be mindful of.
Is there a winner?
Just like before, answering this question is difficult; both Azure and Google Cloud have you covered for all the main cloud computing pillars that you’d expect.
If you are already invested in Microsoft technology, then Azure is the natural choice as it’ll complement your existing infrastructure and tooling. If you need to leverage complex AI routines to process big data with images, again, Azure is the more sensible option.
If you want to opt for a more mature cloud computing platform, you can’t go wrong with GCP. It has evolved organically as the firm grew its line of products and services and continues to do so. Azure is the new kid on the block but is equally a good match.
In this blog post, we’ve looked at how the Google Cloud Platform and Microsoft Azure compare with each other, and now that we’ve examined all three main cloud offerings, you should be more informed as to which platform is most suitable for you or your business.
If you’d like more information or are looking for guidance, feel free to contact our sales team!