Why the 'Best Cloud' Question Is the Wrong Question
The hyperscaler market has matured to the point where AWS, Azure, and GCP all offer the core services needed for automotive cloud workloads. The right question is not 'which is best?' but 'which is best for our specific workload profile, our existing ecosystem, and our organizational capabilities?'
This article provides a structured comparison across the dimensions that matter most for automotive enterprises. We have no financial relationship with any of the three providers — our assessments are based on project experience with all three.
Full Platform Comparison for Automotive Workloads
AWS vs Azure vs GCP: Automotive Workload Comparison
| Factor | AWS | Microsoft Azure | Google Cloud |
|---|---|---|---|
| Connected car / IoT | AWS IoT Core, Greengrass (strong) | Azure IoT Hub, IoT Edge (strong) | Cloud IoT Core (limited; being deprecated) |
| SAP workloads | Good (AWS SAP certified) | Best (RISE with SAP primary partner) | Good (SAP certified) |
| Data & analytics | Strong (Redshift, Glue, Kinesis) | Strong (Synapse, Event Hub) | Best (BigQuery, Dataflow, Vertex AI) |
| Kubernetes / containers | EKS (mature) | AKS (mature) | GKE (market leader) |
| German data residency | EU-WEST-1, EU-CENTRAL-1 (Frankfurt) | Germany North, Germany West Central | europe-west3 (Frankfurt) |
| TISAX-accepted regions | Yes (Frankfurt, Ireland) | Yes (Germany North) | Yes (Frankfurt) |
| OEM enterprise agreements | Most common | Common (via Microsoft EA) | Growing |
| DevOps tooling | CodePipeline, CodeBuild (adequate) | Azure DevOps (strongest) | Cloud Build (adequate) |
| Pricing (compute-general) | Baseline reference | ~5–10% higher for comparable specs | ~5–15% lower for compute-heavy |
A few key observations from the table: Google Cloud IoT Core is in the process of being deprecated, making GCP a weak choice for new connected vehicle projects. Azure has the strongest enterprise agreement coverage in European automotive enterprises thanks to existing Microsoft licensing relationships. AWS has the most mature automotive partner ecosystem and is the most common choice for greenfield connected car projects.
Our Recommendations by Use Case
**Connected Car Platform (new build)**: AWS IoT Core or Azure IoT Hub. Both are production-proven at OEM scale. Choose AWS if you want maximum partner ecosystem breadth; choose Azure if you have strong existing Microsoft integration.
**SAP on Cloud**: Azure (RISE with SAP primary) or AWS (second choice). Azure's RISE relationship gives it first-mover advantage in SAP managed cloud, though AWS has significant SAP delivery experience.
**Data Analytics and ML**: GCP (BigQuery is industry-leading) or AWS (comprehensive data services). Azure Synapse is a credible alternative for organizations already in the Azure ecosystem.
**Manufacturing Edge Computing**: AWS (Greengrass) or Azure (IoT Edge). Both have mature edge runtime solutions for factory floor deployment.
**Multi-cloud (large enterprises)**: Inevitable for most OEMs. Design for cloud-agnostic layers where possible (Kubernetes, Terraform, open message standards) and accept managed service lock-in only where the productivity gain is clear.
What About Sovereign and Regulated Cloud Options?
For automotive enterprises with strict data sovereignty requirements — particularly those handling classified defense supply chain data or highly sensitive prototype information — sovereign cloud options exist:
**AWS**: AWS GovCloud (US), AWS Dedicated Local Zones (Europe), AWS Sovereign Cloud (announced for EU) **Azure**: Azure Government, Azure Germany (operated by T-Systems, being phased out), Azure Sovereign regions **GCP**: Google Distributed Cloud (edge/air-gapped deployments)
For most German automotive suppliers, standard AWS Frankfurt, Azure Germany North, or GCP Frankfurt regions are sufficient for TISAX Level 2 requirements. Level 3 (highly sensitive prototype data) may require additional controls but rarely requires a fully sovereign cloud deployment.