Deciding between cloud service providers can be challenging, as they all offer services that appear similar on the surface.
Google Cloud and Amazon Web Services (AWS) are two cloud service providers that offer a robust suite of services designed to power businesses of all sizes, with Microsoft Azure being another strong contender. However, you need to understand how they differ in terms of features, pricing, and performance to choose the best fit for your needs.
Whether you’re a startup, a growing business, or an established enterprise, taking the time to understand these cloud platforms is a step you can’t afford to skip.
Choosing between Google Cloud and AWS isn’t straightforward due to their deep integration with different ecosystems, varied market shares, and distinct service offerings. To make matters even more complicated, each option is best suited for specific use cases that you need to be aware of.
This article will outline the differences between Google Cloud vs. AWS and explain what you need to know to make an informed decision.
An Overview of Google Cloud and AWS
Here’s an overview to help you understand the key offerings of each platform:
Amazon Web Services (AWS)
AWS (Amazon Web Services) started as a subsidiary of Amazon in 2006, initially offering infrastructure services such as storage and compute power. Over the years, AWS evolved into a one-stop solution as a cloud computing platform, providing a wide range of services that cater to different business needs, including computing, storage, databases, machine learning, and more. It has an extensive AWS global infrastructure, making it a reliable choice for businesses worldwide.
Image Source: Amazon Web Services
Key offerings include:
- Compute: Amazon Elastic Compute Cloud (EC2) is one of the flagship services of AWS. It allows users to run virtual servers in the cloud, with flexible configurations for CPU, memory, storage, and networking. EC2 supports various operating systems and provides options for auto-scaling and load balancing.
- Storage: AWS offers storage solutions like Amazon S3, which provides highly scalable object storage with industry-leading durability, security, and performance. Amazon S3 is ideal for data backup, archiving, and content distribution.
- Database: Amazon Relational Database Service (RDS) simplifies the process of setting up, operating, and scaling relational databases in the cloud. It supports various database engines, like MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.
- Big Data and analytics: AWS provides extensive Big Data services, including Amazon Redshift, a fast, fully managed data warehouse that makes it simple and cost-effective to analyze large datasets using SQL-based queries. It seamlessly integrates with other AWS services such as S3 and EC2, enhancing data processing and analytics capabilities for real-time insights and business intelligence.
- Container service: Amazon Elastic Container Service (ECS) simplifies the deployment and management of containerized applications. ECS is highly scalable and integrates well with other AWS services.
- Serverless computing: AWS Lambda allows developers to run code without provisioning or managing servers. It automatically scales applications by running code in response to triggers and events. This reduces operational overhead and helps with rapid development.
- Machine learning: Amazon SageMaker is a fully managed service that enables developers and data scientists to build, train, and deploy machine learning models at scale. It integrates with other AWS services and supports popular frameworks.
AWS has over 200 services available — explore more about their offerings here.
Google Cloud
Launched in 2008 and recently re-named, Google Cloud is a suite of cloud computing services that operates on the same infrastructure that Google uses internally for its products, such as Google Search, Gmail, and YouTube.
Google Cloud has evolved into a comprehensive cloud platform designed to meet the needs of businesses across different industries, including computing, data storage, machine learning, and advanced analytics. Known for its focus on scalability, performance, and security, Google Cloud has become a preferred choice for organizations seeking powerful and reliable cloud solutions.
Image Source: Google Cloud
Key offerings include (but aren’t limited to):
- Compute: Google Compute Engine provides virtual machines that run on Google’s global infrastructure, offering flexible options for CPU, memory, and disk configurations. It supports auto-scaling, load balancing, and integrates seamlessly with other Google Cloud services.
- Kubernetes: Google Cloud pioneered managed Kubernetes with Google Kubernetes Engine (GKE), which simplifies the deployment, management, and scaling of containerized applications. GKE also integrates seamlessly with other Google Cloud services.
- BigQuery: Google BigQuery is a serverless, highly scalable, and cost-effective multi-cloud data warehouse. It allows organizations to analyze large datasets in real-time using SQL-like queries, and it integrates well with other Google services such as Google Cloud Storage and Google Dataflow.
- Networking: Google Cloud services include Global Load Balancing, which distributes traffic across multiple locations to ensure high availability and reliability. The Virtual Private Cloud (VPC) allows for secure and customizable network configurations, enhancing overall network performance.
- AI and machine learning: Google Cloud offers a suite of AI and machine learning tools, such as AI Platform, Vision AI, and Video AI (all under Vertex AI). These services enable developers to build and deploy machine learning models, automate image and video analysis, and incorporate advanced AI capabilities into their applications.
- Security: Google Cloud is known for its security-first approach, offering features like Identity and Access Management (IAM), encryption at rest and in transit, and a global network with low-latency connections, ensuring businesses can maintain data integrity and privacy at all times. Google Cloud’s Security Command Center gives you a comprehensive view of security and data risks across your entire organization, allowing for proactive threat detection and management.
For more information on Google Cloud offerings, check out the official Google Cloud documentation.
AWS vs. Google Cloud Pricing Overview
Both AWS and Google Cloud offer flexible pricing models designed to suit different business needs, but they approach pricing in slightly different ways.
Free trials and free tiers
AWS provides a variety of free trials for individual services, with varying durations depending on the service. It also offers a 12-month free tier for new users, providing limited usage of key services like EC2, S3, and RDS. Additionally, AWS has a free-forever tier that provides ongoing access to a selection of services such as Lambda and DynamoDB, with monthly usage limits.
Google Cloud, on the other hand, offers a $300 free credit for 90 days, which can be used across a wide range of services, making it ideal for testing or learning the platform. Google also has a free tier for continuous access to certain services like Cloud Functions and BigQuery, with varying usage limits.
On-Demand (pay-as-you-go)
Both platforms follow a pay-as-you-go model, where you only pay for what you use without any upfront commitments. Some services are charged on a per-second basis and some on a per-hour basis. It’s important to do your research on these before you start using them.
Commitment plans
AWS offers two primary options for committed use: Reserved Instances and Savings Plans, both of which provide significant discounts for committing to usage over one or three years.
Google Cloud similarly offers committed use discounts (CUDs) which can be purchased in one- or three-year terms. CUDs come in two forms, with both resource-based and spend-based options available. Google Cloud also automatically applies sustained use discounts when services are used consistently, reducing costs without requiring upfront commitments.
Spot Instances/Preemptible VMs
Both AWS and Google Cloud offer huge discounts (up to 90%) on spare compute capacity through Spot Instances (AWS) and Spot VMs (Google Cloud)). AWS spot instances are billed per-second or per-hour, while Google Cloud uses per-second billing for its preemptible VMs.
AWS vs. Google Cloud: The Comparison Table
| Category | AWS | Google Cloud |
| Market Share | Amazon Web Services (AWS) maintains the highest market share at 31%. | Google Cloud is ranked at the third position with approximately 11% of market share. |
| Free Tier Services | 12-month free tier (e.g., EC2, S3) and Always Free options like DynamoDB and Lambda | $300 credit for 90 days for new users, plus Always Free tier for select services like BigQuery |
| Global Infrastructure | AWS supports 33 regions, 105 availability zones, over 600 points of presence for CloudFront, and serves 245 countries. | Google Cloud supports 40 regions, 121 zones, 187 edge locations, and serves over 200 countries. |
| Compute Services | Amazon EC2 for scalable virtual machines, Elastic Beanstalk for automatic scaling. | Google Compute Engine for VMs, Google App Engine or Cloud Run for PaaS |
| Containerization | Amazon ECS and EKS (Elastic Kubernetes Service) for managing containerized applications. | Google Kubernetes Engine (GKE) – strong integration with Kubernetes (Google is the originator of Kubernetes). |
| Serverless Computing | AWS Lambda for running functions without managing servers. | Google Cloud Functions for event-driven serverless workloads. |
| Machine Learning | Offers a wide suite of ML and AI services including Amazon SageMaker, Augmented AI, Amazon Bedrock, Amazon Lex, and Amazon HealthLake. | Google Cloud AI/ML services, including AutoML and TensorFlow under Vertex AI. Stronger integration with Google products and AI expertise. |
| Data & Analytics | Amazon Redshift for data warehousing, EMR for big data processing, Athena for SQL queries on S3. | BigQuery for serverless data warehousing, Dataflow for real-time data processing. Google Cloud is strong in analytics due to its history with search and advertising data. |
| Storage Options | S3 for object storage, EBS for block storage, Glacier for long-term archive storage. | Cloud Storage for object storage, including Nearline and Coldline options for long-term storage. Persistent Disks (PD) for block storage, |
| Networking | AWS VPC for private networking, Direct Connect for dedicated connections, Global Load Balancing. | Google VPC with Global Load Balancing, Dedicated Interconnect for high-speed connections. Google Cloud’s network is renowned for performance due to its global fiber network. |
| Security | AWS Identity and Access Management (IAM), Shield for DDoS protection, KMS for key management, extensive compliance certifications. | Google Cloud IAM, Cloud Armor for DDoS protection, Cloud KMS for encryption. Google emphasizes security by design with its internal infrastructure. |
| Hybrid & Multi-Cloud | AWS Outposts for hybrid cloud, VMware on AWS for running VMware workloads. | Anthos for managing Kubernetes workloads across hybrid and multi-cloud environments, strong support containers. Google Cloud VMware Engine for lift-and-shift workloads. |
| Developer Tools | AWS CloudFormation for infrastructure-as-code, CodePipeline for CI/CD, CodeDeploy for automated deployments. | Google Cloud Deployment Manager for infrastructure automation, Cloud Build for CI/CD, Cloud Source Repositories for code hosting. |
| Compliance | Extensive certifications including HIPAA, GDPR, SOC, ISO, FedRAMP, PCI DSS. | Similar certifications as AWS but with an edge in certain privacy-focused regions due to Google’s history with data security. You can read more about Google Cloud compliance here. |
| Developer Community & Adoption | Larger and more established developer community with strong industry adoption, especially in large enterprises. | Growing developer community with strong traction in data analytics, machine learning, and AI-driven development. Often chosen for innovation and AI focus. |
Choosing Between AWS and Google Cloud: Key Factors
There’s no one-size-fits-all or best all-round option for everyone. The right cloud vendor for you will depend on your specific needs and preferences. In this section, we break down some factors to consider to help guide your decision.
Specific requirements
AWS provides a broader selection of services, including advanced AI, analytics, and serverless computing power. Its support and advancement in Computing services, AI tools like SageMaker, and a wide range of databases make AWS a solid choice for businesses needing an extensive variety of cloud services.
Google Cloud shines in areas like AI/ML with services such as AutoML and TensorFlow, which are well-integrated into Google’s ecosystem. It’s also a preferred platform for businesses already using Google Workspace, offering seamless integration with tools like Gmail, Google Docs, and Sheets.
Technical expertise
AWS’s dominance in the market is reflected in a larger community and more comprehensive training and support resources. If you’re starting from scratch or have limited in-house expertise, AWS may be more accessible. Additionally, AWS certifications are more in-demand globally, making AWS a good choice for businesses looking for industry-recognized qualifications and a wide selection of third-party learning resources. The AWS Certified Cloud Practitioner certification can also teach you how to use AWS effectively.
For developers already familiar with Google technologies, Google Cloud can be the preferred choice, especially if the organization heavily relies on Google’s tools. Google Cloud offers the Google Cloud Certification, providing foundational knowledge for using Google Cloud services.
When you’re making your decision, remember to evaluate your current and future scalability needs, performance expectations, and flexibility in debugging tools.
Existing cloud expertise
If your developers or operations team are already well-versed with a particular cloud service provider, it makes sense to stick with that provider. Leveraging existing expertise can save significant time and money, as retraining staff on a new provider can be costly and time-consuming. Ultimately, your team can achieve similar results on either platform, so taking the path of least resistance is often the most efficient choice.
Migration discounts
Both platforms offer migration incentives such as credits and bulk pricing discounts. While these offers can reduce initial costs, it’s important to focus on long-term benefits and value rather than one-time savings.
Both AWS and Google Cloud are top-tier providers, and your choice will ultimately come down to which platform aligns best with your business’s strategic goals and operational capacities.
Maximize Your Google Cloud and AWS Investments With ProsperOps
ProsperOps automates your cloud financial management with minimal user intervention.
ProsperOps is the leading FinOps automation platform known for cloud rate optimization. We automatically optimize the hyperscaler’s native discount instruments to reduce your cloud spend and place you in the 98th percentile of FinOps teams.
We help you optimize discount instruments like AWS RIs and Savings Plans, or Google Cloud CUDS by autonomously and dynamically blending them to maximize your savings while minimizing commitment risk.
With ProsperOps, there’s no friction within your operations or forced trade-offs. The algorithm runs silently in the background 24/7, without manual oversight or intervention from your busy teams.
We help you achieve and maintain an Effective Savings Rate (ESR) that can help position your business as a top FinOps performer.
Ready to experience this automation in action? Book a demo today and experience the potential savings and efficiency gains firsthand.
