Google Compute Engine vs Amazon Elastic Compute Cloud

Struggling to choose between Google Compute Engine and Amazon Elastic Compute Cloud? Both products offer unique advantages, making it a tough decision.

Google Compute Engine is a Ai Tools & Services solution with tags like iaas, paas, virtual-machines, scalable-computing.

It boasts features such as Virtual machines, Persistent disks, Networking, Load balancing, Autoscaling, Integrated monitoring and logging and pros including Fast provisioning, Scalability, Preemptible VMs for cost savings, Global infrastructure, Integrates with other GCP services.

On the other hand, Amazon Elastic Compute Cloud is a Ai Tools & Services product tagged with iaas, virtual-machines, aws.

Its standout features include Scalable and resizable compute capacity, Ability to launch virtual server instances, Deployment of applications through Amazon Machine Images, On-demand infrastructure with no upfront commitments, Flexible pricing options, Secure and reliable cloud computing platform, and it shines with pros like Scalability and flexibility to meet changing business needs, Reduced infrastructure management overhead, Reliable and secure cloud environment, Wide range of instance types and configurations to choose from, Integration with other AWS services for a comprehensive cloud solution.

Feature	Google Compute Engine	Amazon Elastic Compute Cloud
Overall Score	N/A	1
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

Google Compute Engine

Description: Google Compute Engine is a scalable computing service that provides virtual machines running in Google's data centers and worldwide fiber network. It delivers consistent performance and uptime for operating systems, application frameworks, and applications.

Amazon Elastic Compute Cloud

Description: Amazon EC2 is a cloud computing service that provides resizable compute capacity in the cloud. It allows users to launch virtual server instances that run on Amazon's infrastructure. EC2 enables scalable deployment of applications by providing a web service through which a user can boot an Amazon Machine Image to configure a virtual machine.

Key Features Comparison

Google Compute Engine Features

• Virtual machines
• Persistent disks
• Networking
• Load balancing
• Autoscaling
• Integrated monitoring and logging

Amazon Elastic Compute Cloud Features

• Scalable and resizable compute capacity
• Ability to launch virtual server instances
• Deployment of applications through Amazon Machine Images
• On-demand infrastructure with no upfront commitments
• Flexible pricing options
• Secure and reliable cloud computing platform

Pros & Cons Analysis

Google Compute Engine

Pros

• Fast provisioning
• Scalability
• Preemptible VMs for cost savings
• Global infrastructure
• Integrates with other GCP services

Cons

• Can be complex to configure
• No desktop OS support
• Pricing not as low as some competitors

Amazon Elastic Compute Cloud

Pros

• Scalability and flexibility to meet changing business needs
• Reduced infrastructure management overhead
• Reliable and secure cloud environment
• Wide range of instance types and configurations to choose from
• Integration with other AWS services for a comprehensive cloud solution

Cons

• Complexity in managing and optimizing costs
• Potential vendor lock-in with AWS ecosystem
• Steep learning curve for new users
• Reliance on internet connectivity for access to resources

Pricing Comparison

Google Compute Engine

• Pay-As-You-Go

Amazon Elastic Compute Cloud

• Pay-As-You-Go