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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesAWS, Azure, and Google Cloud often have services aimed at the same job, but a matching name—or a row in a comparison chart—does not mean they work the same way. Use service maps to find candidates, then compare scope, configuration, access controls, resilience, and management boundaries against your workload. Google’s own table calls its entries “similar or comparable offerings,” while Microsoft cautions that direct mappings are not always clear and that some services exist on only one platform.
What the service names map to—and what they do not
The table below is a starting map of common capabilities, not a promise of feature parity. The listed products can differ in scope, implementation, pricing, regional availability, quotas, and operational behavior. Google Cloud’s comparison page lists generally available services and comparable offerings and was last updated December 3, 2024; check current provider documentation before planning a deployment or migration.
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| Capability | AWS | Azure | Google Cloud | Important qualification |
|---|---|---|---|---|
| Virtual machines | Amazon EC2 | Azure Virtual Machines | Compute Engine | Compare actual CPU, memory, storage, architecture, and pricing configuration. Instance-family labels do not establish equivalent capacity. |
| Object storage | Amazon S3 | Azure Blob Storage | Cloud Storage | Compare authorization, lifecycle rules, redundancy, retrieval behavior, and performance for the specific use case. |
| Virtual network | Amazon VPC | Azure Virtual Network (VNet) | VPC network | Network scope differs: the Microsoft guide describes Google Cloud VPC networks as global and Azure VNets as regional. Plan address ranges and topology before connecting clouds. |
| Application delivery and global traffic | CloudFront or Global Accelerator, depending on need | Front Door or cross-region Load Balancer, depending on layer and scenario | Cloud CDN or other products, depending on function | A product may combine or focus on different capabilities, such as content delivery, web application firewall, DNS, or layer-4 acceleration. Match the function, not just the broad label. |
| Organizational hierarchy | Accounts and organizations | Management groups, subscriptions, and resource groups | Organizations, folders, and projects | These concepts occupy different levels and can govern billing, quotas, policy, or deployment organization in different ways. |
For provider-to-provider discovery, see Google Cloud’s AWS, Azure, and Google Cloud service comparison and Microsoft’s Azure for Google Cloud professionals. The comparison is illustrative, not an exhaustive catalog; verify each service’s current status, region, tier, quota, and price with its provider.
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Why a functional match is not an interchangeable service
Two products can solve a similar problem while differing in design, available features, integration points, or management model. Microsoft puts the distinction plainly: “Azure and Google Cloud built their capabilities independently over time, so they have significant implementation and design differences.” Some services have no direct counterpart, and others map to several choices depending on what the workload actually needs.
#1 Best Overall
Start with the outcome you need—such as storing objects, exposing an application globally, or connecting private networks—then compare the specific capabilities and constraints that produce that outcome. A broad service label cannot settle questions about latency, access policy, failure behavior, or operational tooling.
Gotchas that can change a design or migration
VM families do not translate into equal capacity
EC2 instance types and Azure VM sizes have broadly similar categories, but their RAM, CPU, and storage capabilities differ. A family name is not a sizing formula: compare the actual configurations against the workload’s CPU, memory, storage, and architecture requirements, then validate performance for the application. Microsoft’s AWS-to-Azure compute comparison describes these category similarities and configuration differences.
Rank #2
Object, block, and file storage are different patterns
S3, Blob Storage, and Cloud Storage are object-storage services. They are not direct substitutes for block storage such as EBS or managed disks, or shared file services such as EFS, FSx, and Azure Files. First identify whether an application needs object access, a disk attached to a compute instance, or a shared file system; then compare the options within that category.
Even within object storage, access and resilience choices differ. AWS commonly grants access through IAM roles or bucket policies, while Azure Blob access can involve layered controls including the Storage firewall. Temporary access is commonly provided with an AWS presigned URL or an Azure shared access signature. For replication, distinguish local or zone-redundant storage from cross-region copies and check what happens during failover: Microsoft notes that Azure GRS/GZRS secondary-region data is not accessible unless a planned or unplanned failover occurs. See Microsoft’s AWS-to-Azure storage comparison for the provider-specific distinctions.
Rank #3
Network scope and product boundaries are not uniform
Network designs need to account for more than the word “VPC.” The Microsoft cross-cloud guide describes Google Cloud VPC networks as global and Azure VNets as regional. In Microsoft’s AWS/Azure networking comparison, AWS subnets reside in one Availability Zone, while Azure subnets can span multiple Availability Zones. These scope differences affect address planning and topology; inventory routes, traffic flows, IP ranges, DNS, and security controls before connecting environments.
Global delivery is another area where one-to-one mapping can mislead. Azure’s guidance maps AWS Global Accelerator to different Azure choices depending on the layer and scenario: HTTP/HTTPS needs differ from TCP/UDP acceleration. The same guide says VPC Lattice has no single Azure equivalent. Review Microsoft’s AWS-to-Azure networking comparison for these mappings rather than treating “global traffic” as one interchangeable product category.
Projects and subscriptions match only on some axes
Azure resources sit in resource groups, which are organized under subscriptions and management groups. Google Cloud uses projects within folders and organizations. A Google Cloud project is conceptually like an Azure subscription for some billing and quota concerns, but functionally resembles a resource group as a deployment container. Calling one simply the equivalent of the other hides the difference. Microsoft explains the comparison in Azure management for Google Cloud professionals.
How to compare candidates for a real workload
Before choosing a counterpart or planning a migration, compare options along the dimensions that determine whether the workload will work as intended:
Best Value
- Function and required features: Write down the workload outcome and the capabilities it depends on; do not start with a product name.
- Geographic and resource scope: Check supported regions, network boundaries, and how resources are grouped.
- Performance and capacity: Compare actual compute, storage, and network configurations, then validate them against the workload.
- Identity, access, and network security: Review how permissions, temporary access, firewalls, routes, and security controls are configured.
- Resilience and recovery: Check redundancy, replication, failover triggers, and whether replicated data is available before failover.
- Quotas, governance, and billing: Identify which organizational level controls each boundary and what limits apply.
- Migration and operations: Account for changes to deployment, monitoring, automation, and other operational tooling, as well as regional availability.
A service map is useful for building a shortlist. The decision comes from matching the workload’s requirements to the actual configuration and operating model in the target cloud.
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