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There is no universal winner. Start with AWS for breadth and ecosystem, Azure for Microsoft-centric estates, Google Cloud for analytics, Kubernetes and AI, and OVHcloud for European infrastructure, straightforward cloud services and workloads where network-transfer costs matter. Then validate the choice against the services, regions and full workload cost you actually need.
Quick comparison: which cloud should you evaluate first?
| If your priority is… | Start with… | Why |
|---|---|---|
| Broadest managed-service catalog and a large partner and talent ecosystem | AWS | It offers extensive infrastructure and platform choices, with mature patterns for complex and multi-region architectures. |
| Microsoft software, identity and hybrid integration | Azure | It is a natural fit for organizations using Windows Server, SQL Server, .NET, Microsoft 365, Entra ID or Microsoft enterprise agreements. |
| Analytics, Kubernetes and data or AI workflows | Google Cloud | BigQuery, Google Kubernetes Engine and Vertex AI can fit teams centered on analytics and cloud-native engineering. |
| European infrastructure, direct infrastructure pricing or egress-sensitive workloads | OVHcloud | It offers public cloud alongside bare metal and private-cloud options, and selected public-cloud offerings include network traffic. |
| Lowest total cost | Model the workload on each candidate | Region, network, storage, managed services, licensing, discounts and operations all affect the bill. |
These are starting points, not rankings. AWS, Azure and Google Cloud are broad hyperscalers; OVHcloud is a credible option for many infrastructure workloads but does not match every hyperscaler service category. A comparable product name does not establish comparable features, service maturity, availability or operating effort.
What is—and is not—being compared
This comparison covers public-cloud infrastructure and platform capabilities: virtual machines, storage, databases, Kubernetes, serverless, networking, AI, analytics, identity, security, hybrid options, support and commercial models. It does not treat consumer hosting, colocation, or dedicated bare metal as interchangeable with public cloud. Bare metal and private-cloud options matter to provider selection, but their economics and operational model should be compared separately.
Use service categories to shortlist providers, then verify the exact product and configuration. For example, OVHcloud may cover the need for compute, object storage, Kubernetes or a common managed database without being a one-for-one substitute for a hyperscaler’s proprietary analytics, identity or distributed-database services.
#1 Best Overall
Service map: similar labels, different depth
| Capability | AWS | Azure | Google Cloud | OVHcloud |
|---|---|---|---|---|
| Virtual machines | EC2 | Azure Virtual Machines | Compute Engine | Public Cloud instances |
| Object storage | Amazon S3 | Azure Blob Storage | Cloud Storage | Object Storage |
| Block storage | EBS | Managed Disks | Persistent Disk | Block Storage |
| File storage | EFS / FSx | Azure Files / NetApp Files | Filestore | Enterprise File Storage and related services |
| Managed Kubernetes | EKS | AKS | GKE | Managed Kubernetes Service |
| Serverless and containers | Lambda; ECS / Fargate / App Runner | Azure Functions; Container Apps / Container Instances | Cloud Run functions / Cloud Functions naming varies; Cloud Run / GKE | Managed Kubernetes and container-oriented services; verify current serverless options |
| Relational databases | RDS / Aurora | Azure SQL / Azure Database services | Cloud SQL / AlloyDB / Spanner | Managed PostgreSQL, MySQL and selected database services |
| NoSQL and specialized data | DynamoDB and other database services | Cosmos DB | Firestore / Bigtable | More limited managed NoSQL selection |
| Analytics and warehouse | Redshift and related services | Fabric / Synapse-related services | BigQuery | Data Platform and analytics services, with a narrower ecosystem |
| AI platform | Bedrock / SageMaker | Microsoft Foundry / Azure Machine Learning | Vertex AI | AI infrastructure and selected AI services; verify models and GPUs by region |
| Identity and hybrid | IAM / IAM Identity Center; Outposts / EKS Anywhere and related services | Microsoft Entra ID / Azure RBAC; Azure Arc / Azure Local | Cloud IAM; Google Distributed Cloud | IAM and account-management capabilities; bare metal, private cloud and European infrastructure |
Provider product catalogs are the starting point for checking scope: AWS, Azure, Google Cloud and OVHcloud Public Cloud. Product names and packaging can change; confirm the current offer and its regional availability before designing around it.
Why a universal cheapest-cloud verdict fails
A VM’s hourly list price is only one line in a cloud bill. Regional rates vary; AWS notes that costs can differ by region because of factors including land, fiber, electricity and taxes (AWS Well-Architected cost guidance). The same workload can change price materially with its architecture, utilization, license requirements and negotiated terms.
Normalize before comparing
- Choose the same geography, operating system, CPU architecture and approximate instance generation.
- Match utilization and billing assumptions: on-demand, spot/preemptible, reservations, savings plans or committed-use discounts are not interchangeable.
- Match storage capacity, performance, snapshots, backup retention and retrieval behavior.
- Match database node count, high-availability configuration, replicas, I/O and backup policy.
- Include load balancers, NAT, public IPs, cross-zone and cross-region traffic, logging, support, software licenses and data egress.
- Include engineering and operations labor if a managed service on one platform is being compared with self-managed software on another.
Each provider publishes pricing information and a calculator: AWS pricing and AWS Pricing Calculator; Azure pricing and Azure Pricing Calculator; Google Cloud pricing and Google Cloud Pricing Calculator; and OVHcloud Public Cloud pricing. Treat calculator output as an estimate based on your inputs, not a provider-neutral benchmark.
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- Small web app: two or three VMs, load balancer, managed PostgreSQL, object storage, backups and moderate egress in one production region.
- Kubernetes service: three worker nodes, control plane, block storage, load balancer, registry, logs and cross-zone traffic.
- Data or AI workload: object storage, ETL or batch processing, warehouse or model hosting, data transfer, inference volume and idle-capacity assumptions.
- High-availability enterprise service: deployment across three zones, multi-zone database, cross-region backups, private connectivity, WAF, central logging, security monitoring and enterprise support.
OVHcloud’s public-cloud pricing page highlights included inbound traffic and selected outbound-traffic allowances. It also states that the included outbound allowance depends on region, with Asia-Pacific exceptions; check the current terms for the chosen product and location rather than treating traffic as unlimited. Its Managed Kubernetes control-plane pricing is separate from worker nodes, block storage and public IPs. Google Cloud likewise prices network transfers according to factors including region and destination (Google Cloud network pricing). A higher compute price can still produce a lower total when transfer charges differ; the reverse is possible too.
Compute: compare the machine and the way it is billed
A nominal match such as four vCPUs and 16 GB of memory does not prove equal performance. CPU generation, shared versus dedicated resources, burst rules, network bandwidth, local disks and billing granularity can differ. Without a matched application benchmark, compare published specifications—not performance claims.
- AWS: broad instance-family choice and mature purchasing options are useful for varied or specialized architectures.
- Azure: evaluate Windows Server, SQL Server, .NET and Microsoft licensing needs alongside VM rates; contract terms can change the economics.
- Google Cloud: custom machine shapes and integration with data services can suit data-intensive and cloud-native workloads.
- OVHcloud: consider it for straightforward compute, predictable infrastructure pricing and European or bare-metal-oriented deployments; verify instance diversity, accelerator availability and regional reach for specialized requirements.
For GPU workloads, confirm the exact accelerator, memory, quota and capacity in the target region. An advertised VM family is not evidence that the required GPU can be provisioned when and where the application needs it.
Storage and networking: model data movement explicitly
Object-storage comparisons should include durability and replication configuration, versioning, lifecycle and archive tiers, retrieval charges, API requests and cross-region replication. For block and file storage, compare performance tiers, protocols, snapshots, encryption and backup behavior—not just capacity prices.
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Networking costs may include internet egress, inter-zone and inter-region transfer, NAT gateways, load balancers, CDN, private connectivity, IP addresses, DDoS protection and traffic sent to another cloud. These charges can overturn a compute-only comparison, especially for media delivery, analytics pipelines and multicloud designs.
Rank #3
Managed databases: match the topology, not the product name
First identify the actual database requirement: PostgreSQL, MySQL, SQL Server or Oracle compatibility; read replicas; failover; extensions; connection pooling; point-in-time recovery; and whether a globally distributed or specialized NoSQL system is necessary.
- AWS has a broad menu across relational, key-value, graph, document, time-series and warehouse workloads.
- Azure is compelling when SQL Server, .NET, Microsoft identity, Fabric or Microsoft commercial agreements are central.
- Google Cloud offers managed PostgreSQL-compatible options and integration with analytics, as well as globally distributed database patterns.
- OVHcloud is credible for common managed PostgreSQL and MySQL workloads, with a narrower set of proprietary and globally distributed database options.
OVHcloud lists managed MySQL and MongoDB tiers on its Public Cloud pricing page; check region and tier details there. For any provider comparison, normalize node count, storage, IOPS, backup retention, replicas, encryption and connection limits. A single-node database is not an equivalent alternative to a multi-zone, replicated service.
Kubernetes: account for the whole cluster
All four offer managed Kubernetes, but the control-plane price alone says little about cluster cost or operating effort. Compare worker nodes, control plane, load balancers, persistent storage, registry, ingress, autoscaling, upgrades, policy controls, observability, GPU scheduling and multi-cluster management.
- GKE is a strong candidate when managed Kubernetes operations and integration with Google Cloud are priorities.
- EKS fits organizations already standardized on AWS services and IAM.
- AKS is a natural candidate for Microsoft-centric enterprise platforms.
- OVHcloud Managed Kubernetes merits evaluation for European locations, direct infrastructure choices or transfer-sensitive workloads; check support, ecosystem and region-specific feature coverage.
Official service and pricing pages: EKS pricing, AKS pricing, GKE pricing and OVHcloud Managed Kubernetes. A low-cost or separately priced control plane does not make worker nodes and supporting resources free.
AI: separate accelerators, model APIs and platform features
“Best cloud for AI” is too broad to guide a purchase. Compare four layers: GPU or TPU access; the models available to your account and region; managed training and deployment; and enterprise controls such as identity, audit, logging and data governance.
- AWS: Bedrock provides managed foundation-model access; SageMaker-related services support machine-learning workflows. See Bedrock pricing.
- Azure: Microsoft Foundry, Azure OpenAI-related services and Azure Machine Learning can align with Microsoft identity and developer tooling. The current pricing page is Microsoft Foundry pricing.
- Google Cloud: Vertex AI, accelerator infrastructure and BigQuery integration may suit teams already using Google’s data stack. See Vertex AI pricing and Google Cloud AI.
- OVHcloud: evaluate its AI infrastructure and selected services where European infrastructure or cost-sensitive deployments matter; verify the specific model, accelerator and managed features for the target region at OVHcloud AI.
Calculate end-to-end cost with the same model, context and output assumptions, expected request volume, caching and utilization. Include idle GPU time, vector search, data transfer and any separate charges for API features. Model access, accelerator capacity, policy and pricing can vary by location and account; a token rate or GPU-hour alone does not settle the comparison.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Regions, resilience and data sovereignty
Do not compare region counts without checking what “region” and “zone” mean for the provider, and whether each required product is available there. A region may be a provider-defined geography; a zone may represent a distinct failure domain. A service can exist in a region while a specific GPU, database version or model does not.
AWS currently lists 123 Availability Zones across 39 geographic regions and says each region consists of at least three isolated Availability Zones; the provider also distinguishes regions, zones, Local Zones and edge locations on its global infrastructure page. Treat those counts as volatile, not a permanent comparative ranking. For other providers, consult Azure geographies, Google Cloud locations and the OVHcloud product-by-region matrix; each product’s own availability still needs confirmation.
Validate the target geography before committing
- Choose the required country or region based on latency, legal obligations and recovery objectives.
- Check that the exact VM family, managed Kubernetes service, object storage and database tier are available there.
- Check the required GPU, AI model, key-management service and private connectivity in that same geography.
- Verify backup, replication and failover options in a second region, including transfer cost and any service-specific limits.
- For regulated workloads, document data location, processing location, support access, subprocessors, encryption-key control and contractual commitments.
A European provider or data center does not by itself establish sovereignty. Company headquarters, data location, support location, foreign-access laws, key control and contract terms are separate considerations. Likewise, a compliance certification does not make a customer deployment compliant: access controls, encryption, logging, retention, backups and incident response remain part of the customer’s responsibility.
Developer experience, operations and lock-in
- AWS: breadth, marketplace and established integrations are strengths; service sprawl, overlapping options, billing complexity and the need for governance can raise operating burden.
- Azure: Microsoft identity, hybrid tooling and enterprise integration stand out; licensing and product naming or portal changes can complicate planning.
- Google Cloud: analytics, Kubernetes and machine-learning integration can simplify certain cloud-native workflows; proprietary data services can create migration dependencies.
- OVHcloud: European presence, open-source-oriented infrastructure, selected included traffic and a mix of public cloud, bare metal and private cloud are useful differentiators; its managed-service catalog, geographic reach and ecosystem are smaller.
Portability is a spectrum, not a guarantee. Virtual machines are relatively portable; containers are more portable than the infrastructure beneath them; Kubernetes workloads still depend on identity, networking, storage, ingress, observability and policy. Databases, serverless functions and proprietary analytics services are harder to move without redesign. Reproducing IAM, security and operational tooling elsewhere has a cost even when application code moves cleanly.
How to choose: a scenario-specific decision framework
Score each candidate against your own priorities rather than copying a universal ranking. One useful starting weighting is:
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|---|---|
| Required service availability | 20% |
| Total cost of ownership | 20% |
| Regional and sovereignty fit | 15% |
| Reliability and disaster recovery | 10% |
| Security and compliance | 10% |
| Developer and operations experience | 10% |
| Ecosystem, talent and support | 10% |
| Portability and lock-in risk | 5% |
For a startup, give simplicity and cost more weight; for a regulated enterprise, raise sovereignty, support and compliance; for an AI company, prioritize accelerator capacity, model access and data integration.
Common scenarios
- Choose AWS when breadth, unusual managed services, a large ecosystem or established AWS architecture patterns matter most.
- Choose Azure when Microsoft software, identity, hybrid operations or commercial agreements materially shape the platform decision.
- Choose Google Cloud when analytics, Kubernetes, machine learning or Google data products can reduce engineering effort.
- Choose OVHcloud when the workload is mainly infrastructure, common databases or Kubernetes, and European hosting, included traffic on selected offers, bare metal or direct pricing matters more than a vast proprietary service catalog.
- Use multiple providers only when a concrete requirement—such as a superior service for a key workload, geographic separation or an inherited estate—justifies the added platform, security, network and incident-response complexity.
Alternatives beyond these four may fit specific needs: Hetzner or Scaleway for selected European infrastructure workloads, Oracle Cloud Infrastructure for Oracle-centered requirements, DigitalOcean for simpler developer-oriented deployments, Cloudflare for edge delivery and security, or colocation and bare metal for stable, highly utilized workloads. They are not direct equivalents to every service in a hyperscaler catalog.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
