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For most enterprises, selecting both a primary and secondary cloud service is now an important strategy. Recent research shows that northward of 90 percent of enterprises and non-profit organizations are utilizing two or more cloud services accounts. This is a big change over what was happening only a few years ago, when some companies were still reluctant to trust their business data in any cloud application.
Cloud-service providers such as Amazon Web Services, Microsoft Azure, Google, IBM, Dell EMC, Salesforce, Oracle and others are making it easier all the time for customers to come and go or add or subtract capacity or apps as needed. These and other providers also keep coming up with new and more efficient services for companies to use, many of which now feature artificial intelligence options to make them more valuable.
In this article, we take a close look at two of the three largest cloud services providers in the world: Amazon Web Services and Google Cloud Platform.
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What we’ll do here is compare at a high level and in a few different ways these two global cloud storage and computing services, so as to help you decide on the one that suits your company as the most cost- and feature-efficient one available.
AWS vs. GCP: Key Similarities, Differences
To use an AWS service, users must sign up for an AWS account. After they have completed this process, they can launch any service under their account within Amazon's stated limits, and these services are billed to their specific account. If needed, users can create billing accounts and then create sub-accounts that roll up to them. In this way, organizations can emulate a standard organizational billing structure.
Similarly, GCP requires users to set up a Google account to use its services. However, GCP organizes service usage by project rather than by account. In this model, users can create multiple, wholly separate projects under the same account. In an organizational setting, this model can be advantageous, allowing users to create project spaces for separate divisions or groups within a company. This model can also be useful for testing purposes: once a user is done with a project, he or she can delete the project, and all of the resources created by that project also will be deleted.
AWS and GCP both have default soft limits on their services for new accounts. These soft limits are not tied to technical limitations for a given service; instead, they are in place to help prevent fraudulent accounts from using excessive resources, and to limit risk for new users, keeping them from spending more than intended as they explore the platform. If you find that your application has outgrown these limits, AWS and GCP provide straightforward ways to get in touch with the appropriate internal teams to raise the limits on their services.
Resource Management Interfaces
AWS and GCP each provide a command-line interface (CLI) for interacting with the services and resources. AWS provides the Amazon CLI, and GCP provides the Cloud SDK. Each is a unified CLI for all services, and each is cross-platform, with binaries available for Windows, Linux, and macOS. In addition, in GCP, you can use the Cloud SDK in your web browser by using Google Cloud Shell.
AWS and GCP also provide web-based consoles. Each console allows users to create, manage, and monitor their resources. The console for GCP is located at https://console.cloud.google.com/.
Pricing Processes Are Different
One area where there is not a notable difference between these two market leaders is in pricing. AWS uses a pay-as-you-go model and charges customers per hour—and they pay for a full hour, even if they use only one minute of it. Google Cloud follows a to-the-minute pricing process.
Many experts recommend that enterprises evaluate their public cloud needs on a case-by-case basis and match specific applications and workloads with the vendor that offers the best fit for their needs. Each of the leading vendors has particular strengths and weaknesses that make them a good choice for specific projects.
So, let’s get into more specifics.
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What is AWS?
Amazon Web Services (AWS) is a cloud service platform from Amazon, which provides services in different domains such as compute, storage, delivery and other functionality which help the business to scale and grow. AWS utilizes these domains in the form of services, which can be used to create and deploy different types of applications in the cloud platform. These services are designed in such a way that they work with each other and produce a scalable and efficient outcome. AWS services are categorized into three types: infrastructure as a service (IaaS), software as a service (SaaS) and platform as a service (PaaS). AWS was launched in 2006 and become the most-purchased cloud platform among currently available cloud platforms. Cloud platforms offer various advantages such as management overhead reduction, cost minimization and many others.
AWS Pros and Cons, Based on User Feedback
PROS: Amazon's single biggest strength really turned out to be the fact that it was first to market in 2006 and didn’t have any serious competition for more than two years. It sustains this leadership by continuing to invest heavily in its data centers and solutions. This is why its dominates the public cloud market. Gartner Research reported in its Magic Quadrant for Cloud Infrastructure as a Service, Worldwide, that "AWS has been the market share leader in cloud IaaS for over 10 years." Specifically, AWS has been the world leader for closer to 13 years, or ever since it first launched its S3 (Simple Storage Service) in fall 2006.
Part of the reason for its popularity is certainly the massive scope of its global operations. AWS has a huge and growing array of available services, as well as the most comprehensive network of worldwide data centers. Gartner has described AWS as “the most mature, enterprise-ready (cloud services) provider, with the deepest capabilities for governing a large number of users and resources."
CONS: Cost and data access are Amazon's Achilles heels. While AWS regularly lowers its prices—in fact, it has lowered them more than 80 times in the last several years, which probably means they were too high to begin with. Many enterprises find it difficult to understand the company's cost structure. They also have a hard time managing these costs effectively when running a high volume of workloads on the service. And customers, beware: Be sure you understand the costs of extracting data and files once they are in AWS’s storage control. AWS will explain it all up front for you, but know that it’s a lot easier to start a process and upload files into the AWS cloud and access apps and services than to find data and files you need and move them to another server or storage array.
In general, however, these cons are outweighed by Amazon's strengths, because organizations of all sizes continue to use AWS for a wide variety of workloads.
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What is Google Cloud Platform?
For the past 15 years, Google has been building one of the fastest, most powerful, and highest-quality cloud infrastructures on the planet. Internally, Google itself uses this infrastructure for several high-traffic and global-scale services, including Gmail, Maps, YouTube and Search. Because of the size and scale of these services, Google has put a lot of work into optimizing its infrastructure and creating a suite of tools and services to manage it effectively. GCP puts this infrastructure and these management resources at users’ fingertips.
Google Cloud was developed by Google and launched in 2008. It was written in Java, C++, Python including Ruby. It also provides the different services that are IaaS, PaaS and Serverless platform. Google cloud is categorized into different platforms, such as Google App Engine, Google Compute Engine, Google Cloud Datastore, Google Cloud Storage, Google Big Query (for analytics) and Google Cloud SQL. Google cloud platform offers high-level computing, storage, networking and databases.
It also offers different options for networking, such as virtual private cloud, cloud CDN, cloud DNS, load balancing and other optional features. It also offers management of big data and Internet of things (IoT) workloads. Cloud machine learning engine, cloud video intelligence, cloud speech API, cloud Vision API and others also utilize machine learning in Google cloud. Suffice to say there are numerous options inside Google Cloud, which is most often used by developers, as opposed to line-of-business company employees.
Google Regions and Zones
Nearly all AWS products are deployed within regions located around the world. Each region comprises a group of data centers that are in relatively close proximity to each other. Amazon divides each region into two or more availability zones. Similarly, GCP divides its service availability into regions and zones that are located around the world. For a full mapping of GCP's global regions and zones, see Cloud Locations.
In addition, some GCP services are located at a multi-regional level rather than the more granular regional or zonal levels. These services include Google App Engine and Google Cloud Storage. Currently, the available multi-regional locations are United States, Europe and Asia.
By design, each AWS region is isolated and independent from other AWS regions. This design helps ensure that the availability of one region doesn’t affect the availability of other regions, and that services within regions remain independent of each other. Similarly, GCP's regions are isolated from each other for availability reasons. However, GCP has built-in functionality that enables regions to synchronize data across regions according to the needs of a given GCP service.
AWS and GCP both have points of presence (POPs) located in many more locations around the world. These POP locations help cache content closer to end users. However, each platform uses their respective POP locations in different ways:
- AWS uses POPs to provide a content delivery network (CDN) service, Amazon CloudFront.
- GCP uses POPs to provide Google Cloud CDN (Cloud CDN) and to deliver built-in edge caching for services such as Google App Engine and Google Cloud Storage.
GCP's points of presence connect to data centers through Google-owned fiber. This unimpeded connection means that GCP-based applications have fast, reliable access to all of the services on GCP, Google said.
Google Cloud Platform: Pros and Cons Based on User Feedback
PROS: Users count heavily on Google’s engineering expertise. Google has an exemplary offering in application container deployments, since Google itself developed the Kubernetes app management standard that both AWS and Azure now offer. GCP specializes in high-end computing offerings such as big data, analytics and machine learning. It also provides considerable scale-out options and data load balancing; Google knows what fast data centers require and offer fast response times in all of its solutions.
CONS: Google is a faraway third-place in market share (8 percent; AWS is at 33 percent, Azure at 16 percent), most likely because it doesn't offer as many different services and features as AWS and Azure. It also doesn't have as many global data centers as AWS or Azure, although it is quickly expanding. Gartner said that its "clients typically choose GCP as a secondary provider rather than a strategic provider, though GCP is increasingly chosen as a strategic alternative to AWS by customers whose businesses compete with Amazon, and that are more open-source-centric or DevOps-centric, and thus are less well-aligned to Microsoft Azure."
This is a high-level comparison of two of the top three major cloud service leaders here in mid-2019. We will be updating this article with new information as it becomes available, and eWEEK will also be examining in closer detail the various services—computing, storage, networking and tools—that each vendor offers.
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eWEEK is creating a new series of articles which examine all sectors of IT and present up-to-date research and analysis on the leading companies in each space. It's all designed for enterprise buyers of hardware, software, services and cloud products to have more and better information in hand when the time comes to make an investment.