The Short Answer on Cloud Provider Selection in Europe
For European companies evaluating AWS, Azure, and GCP in 2026: AWS wins on breadth of services and ecosystem maturity; Azure wins for Microsoft-integrated enterprises and hybrid scenarios; GCP wins on data analytics, machine learning, and networking efficiency. All three are GDPR-compliant and offer EU data residency. Your existing technology stack and team skills should heavily influence the decision — switching cloud providers is expensive, so get this right upfront.
According to Gartner's 2025 Magic Quadrant for Cloud Infrastructure and Platform Services, AWS and Azure lead in ability to execute, with GCP accelerating rapidly on data and AI capabilities. European market share data shows AWS at approximately 35%, Azure at 28%, and GCP at 11%, with the remainder split among regional providers.
European Data Centres: Where Your Data Lives
All three major providers have significant European infrastructure, but the distribution matters for latency, compliance, and availability zone coverage:
AWS European Regions
- EU (Ireland) — eu-west-1 — 3 Availability Zones
- EU (Frankfurt) — eu-central-1 — 3 AZs
- EU (London) — eu-west-2 — 3 AZs
- EU (Paris) — eu-west-3 — 3 AZs
- EU (Stockholm) — eu-north-1 — 3 AZs
- EU (Milan) — eu-south-1 — 3 AZs
- EU (Spain) — eu-south-2 — 3 AZs
- EU (Zurich) — eu-central-2 — 3 AZs
Azure European Regions
Azure has the most European regions of the three providers, with 17 European regions including paired regions for disaster recovery in Germany North/West Central, Norway East/West, Switzerland North/West, Sweden Central/South, and more. This breadth is a genuine advantage for organisations with strict data sovereignty requirements in specific countries.
GCP European Regions
GCP has fewer European regions but strong coverage in Belgium, Netherlands, Frankfurt, London, Zurich, Paris, Warsaw, Turin, and Finland. GCP's premium tier network delivers consistently lower inter-region latency than the other providers for global workloads.
GDPR Compliance: What Actually Differs
All three providers offer EU data processing addenda (DPA) and Standard Contractual Clauses (SCCs) required for GDPR compliance. The differences are in the details:
Data Residency Guarantees
- AWS — Data stays in your chosen region by default. No automatic replication across regions. AWS Control Tower provides guardrails to enforce this organisationally.
- Azure — Data residency guarantees documented per service. Azure Policy can enforce regional constraints across subscriptions.
- GCP — Organisation Policy constraints available to enforce data residency. GCP Assured Workloads provides compliance framework support.
Sub-processor Transparency
All three publish sub-processor lists, but update frequency and notification processes differ. Azure provides the most granular sub-processor list with country-level detail, which enterprise procurement and legal teams typically prefer.
Sovereign Cloud Options
- AWS — AWS GovCloud is US-specific. For European sovereignty, AWS European Sovereign Cloud launched in 2024 for regulated industries.
- Azure — Azure Germany was the first "sovereign" cloud in Europe, operated by T-Systems. Microsoft Cloud for Sovereignty provides policy frameworks for sovereign requirements.
- GCP — Sovereign Cloud for France in partnership with Thales; similar partnerships in other European countries.
Service Comparison: The Categories That Matter
Compute
AWS: EC2 has the widest instance type selection — from nano instances to HPC clusters. Graviton3 ARM instances offer the best price-performance for general workloads. Spot Instances provide up to 90% savings for fault-tolerant workloads.
Azure: Strong VM portfolio with seamless integration with Azure Active Directory and Windows Server licensing. Azure Spot VMs equivalent to Spot Instances. B-series burstable VMs excellent for variable workloads.
GCP: Custom machine types allow granular CPU/RAM combinations, useful for right-sizing without over-provisioning. Preemptible/Spot VMs available. C3 instances (Intel Sapphire Rapids) competitive on HPC.
Winner for most European workloads: AWS for variety and maturity; GCP for cost-efficient custom sizing.
Managed Kubernetes
AWS (EKS): Production-grade, broad community support. Configuration is more manual vs GCP. Strong integration with IAM and ECR.
Azure (AKS): Tight integration with Azure AD for RBAC. Good Windows container support. Recent reliability improvements after a rocky 2022–2023.
GCP (GKE): Google invented Kubernetes — GKE is consistently the most feature-complete and operationally mature managed Kubernetes offering. Autopilot mode reduces operational burden significantly.
Winner: GCP GKE for pure Kubernetes capability; AKS if Microsoft identity integration is critical.
Serverless and Functions
AWS (Lambda): Market-leading maturity, broadest runtime support, SnapStart reduces cold start latency. Best ecosystem of triggers and integrations.
Azure (Functions): Strong .NET ecosystem, Durable Functions for stateful workflows. Good integration with Azure Logic Apps and Power Platform.
GCP (Cloud Run / Cloud Functions): Cloud Run's container-first approach is more flexible than function-based models. Excellent for containerised workloads without Kubernetes management overhead.
Winner: AWS Lambda for breadth; GCP Cloud Run for container flexibility.
Data and Analytics
GCP leads significantly in this category. BigQuery remains the most capable analytical database for ad-hoc and large-scale analytics. Vertex AI provides the strongest managed ML platform. Pub/Sub and Dataflow for streaming are excellent. If data is central to your product, GCP deserves serious evaluation even if your other workloads run elsewhere.
Pricing Comparison
Honest pricing comparison is difficult because it depends heavily on discount programmes negotiated and usage patterns. General observations:
- Compute: AWS and GCP are broadly comparable at list price; Azure typically 10–15% higher for equivalent specs. All three offer committed use discounts of 30–50%.
- Storage: GCP Cloud Storage is competitive; S3 standard is slightly higher but has richer feature set. Azure Blob Storage comparable to S3.
- Egress: GCP has the most competitive egress pricing, especially between regions. All three charge for inter-region data transfer — model this carefully for distributed architectures.
- Support: AWS Business Support at 10% of spend; Azure Developer support at €25/month base; GCP Silver support from €150/month. For production workloads, enterprise support contracts with committed spend typically include significant credits.
Decision Framework: When to Choose Each Provider
Choose AWS When:
- You want the broadest service selection and most mature ecosystem
- You value the largest partner network and skills pool in Europe
- You're building on microservices, serverless, or containers without a strong bias toward another provider
- Your team has existing AWS skills — migration cost is real
Choose Azure When:
- You're a Microsoft-heavy organisation (Microsoft 365, Active Directory, Windows Server)
- You have a significant on-premise Microsoft footprint and need hybrid connectivity
- Your development team is .NET focused
- You have Enterprise Agreement credits to use
Choose GCP When:
- Data analytics or machine learning is central to your product
- You're building on Kubernetes and want the best-in-class managed experience
- Cost optimisation is critical and you want the most granular VM sizing
- You're using open source data technologies (Apache Beam, BigTable, Spanner)
Multi-Cloud: When It Makes Sense (and When It Doesn't)
Multi-cloud has genuine use cases — regulatory requirements, avoiding vendor lock-in for specific services, best-of-breed selection. But multi-cloud adds significant operational complexity: your team needs to understand two tooling ecosystems, IAM models, networking models, and billing systems simultaneously. The skills pool for multi-cloud expertise is thin.
Our recommendation: run primary workloads on one provider. Use secondary providers only for specific services where they are clearly superior (e.g., GCP BigQuery for analytics alongside AWS for compute). Don't architect for multi-cloud portability from day one — the abstraction layers required (avoiding provider-specific services) sacrifice too much productivity and capability.
Ready to make the platform decision and start the migration? See our complete cost guide to understand what the migration will cost, or contact our team for a provider-neutral assessment of which platform fits your specific workload portfolio.
