{"id":15697,"date":"2018-05-14T22:34:34","date_gmt":"2018-05-15T02:34:34","guid":{"rendered":"https:\/\/www.sherweb.com\/blog\/?p=15697"},"modified":"2018-08-22T16:36:25","modified_gmt":"2018-08-22T20:36:25","slug":"google-cloud-vs-microsoft-azure","status":"publish","type":"post","link":"https:\/\/www.sherweb.com\/blog\/cloud-server\/google-cloud-vs-microsoft-azure\/","title":{"rendered":"Google Cloud vs. Microsoft Azure: Comparing Cloud Leaders"},"content":{"rendered":"

In a previous blog post, we ran through Azure\u2019s features and compared and contrasted Azure to Amazon\u2019s cloud offering, AWS. In this blog, we continue with this theme and compare the Google Cloud Platform (GCP) with Microsoft Azure.<\/p>\n

The Google Cloud Platform journeyed into the mainstream back in 2011, so it\u2019s been around as long as Microsoft Azure<\/a>.\u00a0 Its initial use was for Google\u2019s backend services like YouTube and the Google search engine.\u00a0 These backend services were ultimately shared with enterprise, and it\u2019s grown as a platform ever since.<\/p>\n

To make the comparison easier, we\u2019ll use the same structure as the previous blog post, and after you\u2019ve read this final comparison, you\u2019ll have a better understanding of the Azure, AWS, and the GCP landscape!<\/p>\n

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Click here to download our free ebook which compares AWS, Google and Microsoft Azure\u00a0<\/a><\/h3>\n

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Computing, Storage, and Databases<\/strong><\/h2>\n

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.\u00a0 Let\u2019s explore these three pillars of Azure and the Google Cloud platform and see how they compare.<\/p>\n

Computing<\/strong><\/h4>\n

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.<\/p>\n

The GCP and Azure both do well in this category, and it\u2019s not surprising as it\u2019s a core component of any cloud computing platform. \u00a0They both have similar on-demand pricing models that charge by the minute, and regarding discount pricing, they operate in very different ways.<\/p>\n

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 \u2013 something to consider if you\u2019re happy to adopt a Microsoft-wide implementation.<\/p>\n

Both support Windows and *NIX images, so you\u2019re good on that front, and as you\u2019d expect, you can provision servers to your unique RAM, SDD requirements and so on.<\/p>\n

Storage<\/strong><\/h4>\n

The Google Cloud Platforms storage mechanism has a few services to handle storage, Google Cloud Storage<\/a>, and Google App Engine Persistence Disks<\/a>.\u00a0 Microsoft Azure\u2019s is called Blob Storage \u2013 both GCP and Azure do well in these categories, and you\u2019d be hard pushed to decide on a winner.<\/p>\n

Databases<\/strong><\/h4>\n

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. \u00a0Both Azure and the GCP offer relational databases or NoSQL databases.\u00a0 Azure\u2019s offering for relational databases is the tried-and-tested SQL Server, and with NoSQL, Azure\u2019s flagship product is called DocumentDB<\/a>, with a low-cost key\/value store called Table Storage<\/a>.<\/p>\n

The GCP relational database service is called CloudSQL<\/a> and is a managed MySQL database whereas the GCP NoSQL offerings are called Cloud Datastore<\/a> and BigTable<\/a>.\u00a0 BigTable drives much of Google\u2019s products and services and can also integrate with Hadoop.<\/p>\n

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\u2019s favour\u00a0 is out-of-the-box support for cross-regional database geo-replication.<\/p>\n

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Developer Support<\/strong><\/h2>\n

We don\u2019t 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.\u00a0 Visual Studio will even automatically provision services for you and create accounts, all from the VS IDE.<\/p>\n

The Google Cloud Platform features a set of Client API libraries, one of which is .NET.\u00a0 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#.\u00a0 The Google Client API library can also be added to a Visual Studio Project as NuGet package<\/a> so downloading and installing it is straightforward.<\/p>\n

To publish to Google Cloud, developers can install Google Cloud Tools<\/a> 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.<\/p>\n

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Machine Learning and Artificial Intelligence <\/strong><\/h2>\n

Machine learning and advancements in artificial intelligence have been growing at rapid rates, so Google and Microsoft have recognised \u00a0the demand for products and services that empower software firms and businesses with the ability to effectively take machine learning algorithms \u201coff the shelf\u201d. \u00a0It is often in the form of a REST API endpoint and easily integrates with their existing tech stack.<\/p>\n

Just some of the areas in which cognitive intelligence can be added, include, but are not limited to:<\/p>\n