Independent comparison for enterprise buyers. Updated May 2026.
Quick verdict: Choose AWS for the broadest service catalogue, largest partner ecosystem, and longest production track record. Choose Google Cloud for data analytics with BigQuery, AI workloads using Vertex AI and Gemini, and Kubernetes maturity through GKE. The differentiator is workload fit: AWS is the broadest default; Google Cloud is the data-and-AI-leaning specialist.
| Criteria | AWS | Google Cloud |
|---|---|---|
| Rating | 4.5 / 5.0 (14,300 reviews) | 4.3 / 5.0 (7,200 reviews) |
| Market Share | Approximately 31% global IaaS/PaaS | Approximately 11% global IaaS/PaaS |
| Regions | 33 regions, 105 availability zones | 40+ regions worldwide |
| Compute | EC2, Lambda, Fargate, ECS, EKS | Compute Engine, Cloud Run, Cloud Functions, GKE |
| Data Warehouse | Redshift | BigQuery |
| AI Platform | Bedrock, SageMaker, Q | Vertex AI, Gemini API |
| Kubernetes | EKS | GKE (Kubernetes originated at Google) |
| Networking | VPC, Transit Gateway, Cloud WAN | VPC, Cloud Interconnect, Cross-Cloud Network |
| Cost Optimisation | Savings Plans, Reserved Instances | Committed Use Discounts, Sustained Use |
AWS offers more than 200 services across compute, storage, databases, networking, analytics, AI/ML, security, IoT, and developer tools. The breadth of the catalogue is the platform's defining feature. AWS Bedrock provides managed access to foundation models from Anthropic, Meta, Mistral, Cohere, and Amazon. SageMaker is the platform for custom model training and deployment. EKS provides managed Kubernetes with mature multi-AZ support.
Google Cloud takes a focused approach with strengths in data analytics, AI/ML, and Kubernetes. BigQuery is widely regarded as the leading cloud data warehouse for serverless analytics at petabyte scale, with separation of storage and compute, in-memory BI Engine, and native ML through BigQuery ML. Vertex AI provides managed model training, deployment, and Gemini-based generative AI. GKE benefits from Kubernetes originating at Google and remains a strong choice for container workloads.
For compute, both platforms offer mature VM, container, and serverless options. AWS Lambda has broader runtime support and longer track record. Google Cloud Run offers a more developer-friendly serverless container model. EKS and GKE are both mature, with GKE Autopilot offering a fully managed control plane for organisations wanting less operational overhead.
For data analytics, Google BigQuery leads on serverless architecture and ease of use. AWS Redshift has improved with RA3 nodes, Serverless mode, and Spectrum but retains more cluster management overhead. Snowflake and Databricks run on both clouds with similar performance characteristics, making the warehouse choice partly orthogonal to cloud choice.
For AI, Google Cloud's tight integration of Gemini with Vertex AI and Workspace gives it an edge in customers building on Google's foundation models. AWS Bedrock provides broader third-party model choice including Anthropic Claude, which has become a leading enterprise foundation model. Both invest heavily in agentic AI.
List prices for comparable services typically vary by 5-15% in either direction. Google Cloud Sustained Use Discounts apply automatically to long-running VMs and can deliver 20-30% savings without commitments, distinguishing GCP from AWS's commitment-based discounts. AWS Savings Plans and Google Cloud Committed Use Discounts both offer 30-72% savings for committed usage.
Five-year total cost of ownership for a mid-size enterprise workload of approximately $1M annual run-rate: comparable within 10-15% before negotiation. Google Cloud often wins on data analytics workloads through BigQuery's serverless pricing model. AWS typically wins on broad-portfolio workloads where service breadth eliminates third-party tooling costs.
Choose AWS when you want the broadest service catalogue, when ISV ecosystem depth matters, when you operate in regions where AWS leads on availability, when you need the most mature production track record, or when your workloads span many service categories beyond compute and data.
Choose Google Cloud when data analytics, BigQuery, and serverless warehousing are central to your strategy, when AI workloads using Gemini or Vertex AI matter, when Kubernetes is your container orchestrator of choice and GKE Autopilot appeals, when sustained use discounts fit your usage pattern, or when you align with Google Workspace.