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How AWS and GCP Compare: The Top 8 Differences

How AWS and GCP Compare: The Top 8 Differences

Cloud technology has become a popular topic in recent years. It offers improved flexibility, security, and scalability. Cloud services also provide various merits like minimization of costs and reduction of management overhead. As a result, users compare cloud technologies in order to get the best services.

Two products always seem to feature prominently in these comparisons: Google’s Cloud Platform (GCP) and Amazon Web Services (AWS).

In this article, we’ll discuss these two popular cloud services at length and highlight their most glaring differences to help you decide which of these giants suits you best.

What is Cloud Computing?

Before we get into the main topic of this article, let’s review:

Cloud computing involves using a network of remote servers hosted on the internet for storing, managing, and processing data in place of a local server or PC.

Google Cloud Platform (GCP)

The Google Cloud Platform Logo.

GCP has been a strong player in cloud hosting since its launch in 2008. GCP is composed of Java, C++, Python, and Ruby. GCP is one of the fastest and strongest top-quality cloud infrastructures the world has to offer. Google utilizes this infrastructure for many highly sought-after worldwide services like YouTube, Gmail, search, and maps.

Because of the magnitude of these services, Google has dedicated a lot of time and effort to perfecting its infrastructure and developing a list of tools and services to help manage them properly. GCP makes these tools and infrastructure available to its users.

Amazon Web Services (AWS)

The Amazon Web Services logo.

AWS started in 2006, so it predates GCP. AWS is a cloud-service platform that provides services in various domains like delivery, computing, and storage, all of which aid in the development and scaling of businesses. AWS offers services that enable developers to create and position various kinds of apps in the cloud platform; this is called application migration.

AWS services are of three types: software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS).

The Top 8 Differences Between AWS and GCP

AWS and GCP are two of the three top competitors in the field of cloud computing (the third is Microsoft Azure). They share a few similarities, each with at least a hundred products and services in their catalog. All of these services effectively aid customers working with cloud technologies. However, AWS and GCP also have several notable differences.

Let’s look at a detailed comparison of some of their most popular products and services:

1. Kubernetes

Kubernetes (K8s) is a free system that helps to automatically deploy, manage, scale, and orchestrate container apps. Container apps are resources that help run code and its component dependencies.

Kubernetes manages containers and even makes them more portable while providing users with the best possible utilization of resources for app development. Here’s how these two cloud technologies compare in this regard:

  • GCP makes it easier to run Kubernetes as Google has been prominent in developing Kubernetes from its infancy.
  • Elastic Kubernetes services for AWS do not give users access to resource monitoring tools, unlike GCP’s Stackdriver.

2. Storage

Amazon and Google have different ways of tackling cloud storage. To map out the difference between the two, let’s look at their features.


  • Individual items get stored in separate buckets. To retrieve these buckets, the developer gives keys to access them.
  • An AWS S3 bucket is storable, but it depends on factors like availability, proximity, issues with cost relation, and latency. AWS boasts of a large web of interconnected data centers globally. This means higher performance and quicker response times when storing and retrieving data across long distances.

GCP Storage:

  • With GCP storage, users can expect a high level of availability.
  • There is consistency of data across various regions and locations.
  • Users have access to Google developer console projects.

3. Computation

GCP Compute Engine is a host-and-compute service that enables users to scale virtual machines while running workload apps and tasks.

Amazon EC2 (Elastic Compute Cloud) provides users with secure, resizable computing in the cloud. It also offers a variety of options for processors, storage, OS, networking, and purchase models.

Now, let’s look at the instances provided by both companies to note their differences.

GCP Compute Engine

  • Memory Optimized: Providing up to 12TB of space, GCP compute engine is for tasks that are memory intensive.
  • General Purpose: Directed at general workloads, it provides fair price and performance ratios.
  • Accelerator Optimized: GCP is designed for GPU-intensive processes and parallel processing.
  • Compute Optimized: It offers higher performance than the general purpose instance. In addition, it is suitable for compute-intensive workloads.


  • Storage Optimized Instances: In AWS EC2, storage optimized instances are for workloads that perform read/write for data stored locally in large amounts.
  • General Purpose Instances: General purpose instances work best for web servers and provide equal proportions of different functionalities such as computing and networking.
  • GPU/Accelerated Instances: These require extra processors and GPUs to boost hardware performances. AWS EC2 GPU/accelerated instances are for graphics processing and floating-point calculation in need of an enormous amount of processing power.
  • Compute Optimized Instances: These instances function best when they get utilized for high-performance tasks that demand high-speed processors and are compute-intensive. With AWS EC2, compute optimized instances are for tasks like devices, game servers, and media encoding.
  • Memory Optimized Instances: These get powered by AWS Nitro System and are brought to EBS optimized instances. They can best serve you when you require a large amount of data to get processed in the memory.

4. Cloud Functions

Serverless computing is a widespread FaaS instance that does not need virtual machine instances before use.  AWS Lambda is the AWS answer to serverless offerings, while Cloud Functions is GCP’s answer.

  • Google Cloud Functions only work with Node.js, whereas AWS Lambda supports various languages like C, Python, and Java.
  • GCP’s Cloud Functions are easier to run than AWS Lambda. However, AWS Lambda has a speed advantage.

5. Availability

Availability zones should be considered when choosing your Cloud Platform. GCP and AWS offer a wide range of availability in several zones, but what’s the difference?

  • GCP: Google Cloud Platform offers its services in 35 different regions worldwide, along with 106 zones, and is available in over 200 countries. In addition, GCP has nine areas currently under development, meaning GCP could be available in 44 regions by the year 2024.
  • AWS: AWS spans 87 zones within 27 regions and has announced plans for 24 more Availability Zones. AWS has a leg up over GCP as it is available in many more countries around the globe.

6. Machine Learning

AWS and GCP present users with top-tier machine-learning tools that help train, develop, and test a machine-learning model.

7. Age

The most simple comparison between AWS and GCP is their age difference, with AWS beating out GCP by two years. AWS cloud-computing was released in 2006, and GCP was launched in 2008. This gives AWS the upper hand as they had two years without competition in the market.

8. Notable Users

It sometimes helps to know the big companies utilizing the services that we also use. Here are some well-known users of AWS and GCP:


So, there you have it! We discussed the top 8 differences between GCP and AWS. Hopefully, this list helps you to make the perfect choice of the best cloud computing platform for you. Finally, if GCP and AWS don't seem adequate for your needs, there are other alternatives that you can check out, too.

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