Cloud

AWS vs Google Cloud: Which Cloud Platform Should You Choose?

AWS and Google Cloud are both top-tier public cloud platforms, but they lead in different areas. AWS offers the broadest service catalog and the largest market share, making it the default choice for many enterprises. Google Cloud differentiates with best-in-class data analytics through BigQuery, the most advanced Kubernetes platform in GKE, and cutting-edge AI and ML capabilities powered by TPUs and Vertex AI. Your decision should be guided by whether you prioritize ecosystem breadth or specialized strength in data and AI.

AWS

Google Cloud

Feature Comparison

How AWS and Google Cloud stack up across key capabilities.

Service Breadth

AWS leads

AWS

Over 200 services covering every conceivable cloud workload. The most complete catalog available, with first-mover advantage in many service categories.

Google Cloud

Smaller overall service catalog than AWS, but comprehensive coverage for core enterprise workloads. Google Cloud focuses on depth and quality over breadth, with particular strength in data and AI services.

Data Analytics

Google Cloud leads

AWS

Amazon Redshift, Athena, EMR, and Kinesis form a capable analytics stack. Broad set of tools, but each often requires more configuration and management overhead.

Google Cloud

BigQuery is the industry benchmark for serverless data warehousing, offering petabyte-scale analytics with no infrastructure management. Looker, Dataflow, and Pub/Sub round out a tightly integrated analytics ecosystem.

AI & Machine Learning

Google Cloud leads

AWS

SageMaker provides end-to-end ML workflows. Bedrock offers access to foundation models including Anthropic and Meta. Wide range of pre-built AI services for common use cases.

Google Cloud

Vertex AI delivers a unified ML platform with access to Google's proprietary models, including Gemini. Custom TPU hardware provides a performance advantage for large-scale training. Google's deep research heritage drives leading-edge AI capabilities.

Kubernetes

Google Cloud leads

AWS

Amazon EKS is a managed Kubernetes service that integrates well with the broader AWS ecosystem. Capable, but requires more operational configuration than GKE.

Google Cloud

Google Kubernetes Engine (GKE) is widely considered the gold standard for managed Kubernetes. Built by the team that created Kubernetes, GKE offers features like Autopilot mode, multi-cluster management, and the smoothest operational experience available.

Pricing & Cost

Google Cloud leads

AWS

Flexible pricing with On-Demand, Reserved Instances, Savings Plans, and Spot Instances. Powerful cost optimization tools, but pricing can be complex and opaque across hundreds of services.

Google Cloud

More transparent pricing with sustained use discounts applied automatically (no commitment required), committed use discounts for longer terms, and per-second billing. Pricing is generally simpler to understand and predict.

Global Infrastructure

AWS leads

AWS

30+ regions and 100+ availability zones worldwide. The most mature and widely distributed global infrastructure of any cloud provider.

Google Cloud

40+ regions with a growing footprint. Google's private global fiber network (one of the largest in the world) provides low-latency connectivity between regions.

Enterprise Adoption

AWS leads

AWS

The most widely adopted cloud platform with the largest ecosystem of consulting partners, ISVs, and trained professionals. Migrating to AWS is well-understood with abundant tooling and expertise available.

Google Cloud

Growing enterprise adoption, particularly in data-intensive and AI-forward industries. Smaller partner ecosystem and fewer certified professionals compared to AWS, which can impact hiring and support availability.

Pros & Cons

AWS

Strengths

Broadest service catalog with over 200 cloud services
Largest market share and most extensive partner ecosystem
Most mature global infrastructure with proven enterprise scalability
Widest selection of compute, storage, and database options
Abundant talent pool and training resources available

Limitations

Data analytics tools require more configuration than BigQuery
Kubernetes experience on EKS is less polished than GKE
Pricing can be complex and difficult to predict
No automatic sustained use discounts like Google Cloud offers

Best For

Organizations that need the broadest possible range of cloud services, value a mature partner ecosystem, and want the widest talent pool for hiring and support. AWS is especially strong for enterprises with diverse workloads that require many different managed services under one roof.

Google Cloud

Strengths

BigQuery is the leading serverless data warehouse
Best managed Kubernetes platform in GKE
Cutting-edge AI and ML with Vertex AI and custom TPU hardware
More transparent and predictable pricing with automatic discounts
Google's private global fiber network delivers exceptional performance

Limitations

Smaller overall service catalog compared to AWS
Smaller partner ecosystem and fewer certified professionals
Enterprise sales and support have historically lagged AWS
Less established migration tooling and fewer reference architectures

Best For

Data-driven organizations where analytics, machine learning, and Kubernetes are core to the business. Google Cloud excels for companies building modern, data-intensive applications, running large-scale analytics with BigQuery, or adopting Kubernetes-native architectures. Startups and enterprises focused on AI innovation often find Google Cloud offers a compelling performance-to-cost ratio.

Our Verdict

Choose AWS if you need the widest range of cloud services, the most extensive partner ecosystem, and a platform that supports virtually any workload imaginable. Choose Google Cloud if data analytics, artificial intelligence, Kubernetes-native architectures, or transparent pricing are your top priorities. Organizations building data-driven products or running large-scale analytics workloads often find Google Cloud delivers better performance per dollar in those areas.

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Frequently Asked Questions

Is Google Cloud ready for enterprise production workloads?

Yes. Google Cloud runs some of the world's largest production workloads and has invested heavily in enterprise features, compliance certifications, and support programs. Organizations like PayPal, Target, and Deutsche Bank run critical workloads on Google Cloud. The platform is fully enterprise-grade, though AWS still has a larger enterprise customer base overall.

How does BigQuery compare to Amazon Redshift?

BigQuery is serverless and requires no infrastructure management, scaling automatically to handle petabyte-scale queries. Redshift offers strong performance but requires cluster sizing, maintenance, and more hands-on management. For organizations that want simplicity and speed with large-scale analytics, BigQuery typically delivers faster time to value.

Which platform is more cost-effective?

It depends on your workload. Google Cloud's sustained use discounts and transparent pricing often result in lower costs for steady-state compute workloads. AWS can be more cost-effective when you take advantage of Spot Instances or Reserved Instances for predictable workloads. We model total cost of ownership for both platforms as part of our advisory engagement.

Can Catch Advisors help us evaluate AWS and Google Cloud?

Yes. As a vendor-neutral advisor, we assess both platforms against your workloads, data strategy, and business requirements. We help with cloud strategy, pricing negotiations, and migration planning at no cost to you, with no obligation to either provider.

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