In an era where cloud computing has become ubiquitous across nearly every industry around the globe, cloud computing giants Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure hurriedly jockey for market share. For enterprise organizations looking for robust scalability and computing horsepower to fuel their digital transformations, these three reign supreme. In fact, even in the middle market, these giants are commonly leveraged over smaller cloud providers. The rationale is simple: near-limitless scalability, enterprise-grade security protocols, and cloud development tools to suit even the most demanding business scenarios. Each of these Infrastructure-as-a-Service (IaaS) platforms offers slightly different technology and functionality; in this piece we examine the various use cases optimized for each.
When deciding which IaaS provider to choose, we must primarily concern ourselves with the wants and needs of the organization in question. AWS has long reigned supreme as the leader in market share among the so-called “big 3” providers, and with good reason: the tech giant wins across the board in the breadth and depth of its services. Offering a staggering 175 services across compute, storage, database, analytics, networking, mobile, developer tools, management tools, IoT, and security, few stones have been left unturned. In terms of developer functionality, AWS wins hands-down. It is no surprise then that the majority of cloud-based applications developed today are powered by AWS. However, the pricing scheme can present challenges to management teams who don’t fully understand the implications of running sophisticated architectures and the associated costs to support storage and compute functions.
In the past 5 years, Microsoft has steadily gained market share against titan AWS with its increasingly-versatile Azure cloud offering. For C-suite teams already customers of Microsoft for Office 365 services, Azure is a popular choice to leverage enterprise-grade cloud computing services all under one umbrella. By combining Teams, Office 365, and Azure, Microsoft has positioned itself as a strong number 2 to AWS, and continues to upgrade its offerings. Chief among these novel solutions is Azure Synapse Analytics (ASA), a robust all-encompassing data warehousing and analytics platform. Compared to Google Big Query and AWS Redshift, two of the leading data warehousing solutions, ASA offers unparalleled performance when executing queries across enormous data sets. For these reasons, Azure is a no-brainer for Microsoft houses looking to expand into the cloud.
Legendary tech powerhouse Google is also no stranger to cloud computing, pioneering search and advanced deep learning technologies across the modern internet ecosystem. Google Cloud Platform (GCP) has positioned itself as a more niche provider when compared to the aforementioned leaders of the industry. Despite lacking the eyebrow-raising breadth of services afforded by other platforms, GCP offers a one-stop AI platform powered by the popular Tensorflow library. For organizations seeking an integrated source of AI and machine learning capabilities alongside translation, search, and security, GCP is an unbeatable solution in the current marketplace. In addition, the platform offers quick-boot virtual machines running on best-in-class Google data centers.
The fierce competition in the cloud computing industry means the latest and greatest cloud functionality at reasonable prices for enterprise and middle market organizations alike. For access to a seemingly-endless array of offerings across compute, storage, IoT and mobile development, AWS still reigns supreme. For organizations already using Microsoft tools such as Teams and Office 365, Azure offers a slew of cloud tools integrated under a single roof. For organizations looking for best-in-class AI and machine learning tools, GCP is a no-brainer. For many larger organizations, a hybrid cloud approach, using one or multiple of the “big 3” in tandem with open source offerings, affords the broadest functionality. In the next installment, we will examine leading proprietary and open source data warehousing solutions.
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