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Google Cloud, AWS, and Azure each offer a framework for planning cloud migrations, but their documented tools are organized differently. Google Cloud’s Migration Center is a central assessment and planning hub linked to tools for moving virtual machines, databases, data, and applications. AWS groups migration guidance by planning, business-case analysis, application mobility, and data mobility. Azure lays out a five-stage migration journey around Azure Migrate and workload-specific guidance. The right choice depends on the workload and target architecture—not a universal ranking.
How the providers organize migration and modernization
| Provider | Documented framework | What the framework covers | What it does not establish |
|---|---|---|---|
| Google Cloud | Migration Center | Cost estimation, asset discovery and assessment, dependency mapping, planning, and technical-fit recommendations; strategies include rehost, replatform, and refactor. Google describes Migration Center as an entry point, not a single tool that carries out every migration. | A universal migration tool or a provider-wide price advantage. (Google Cloud Migration Center documentation.) |
| AWS | Four migration concerns: discovery and planning, business-case analysis, application mobility, and data mobility | A framework for finding and planning work, evaluating its business case, and moving applications and data. AWS describes the tools as supporting rehosting, refactoring, and modernization. | A verified one-to-one feature match against every Google Cloud or Azure service. The AWS guidance reviewed does not establish one. |
| Azure | Plan, Prepare, Execute, Evaluate, and Decommission | A migration journey that links to Azure Migrate, scenarios for on-premises and other-cloud workloads, and landing-zone, governance, and architecture guidance. | That migration ends at data movement. The framework also points to the preparation and operating controls needed around workloads. |
The comparison is based on official provider documentation and Google’s October 5, 2026 portfolio announcement. Provider descriptions establish intended scope, not independently tested performance. They do not provide a like-for-like price ranking or establish current availability in every region.
Which Google Cloud tools map to common workload paths?
Choose a tool by source, destination, and the degree of change you want to make. A VM move, a database migration, and an application rewrite are different projects, even if they are part of the same cloud program.
Virtual machines
Migrate to Virtual Machines moves virtual machines from documented sources such as on-premises VMware and other cloud environments to Compute Engine. This is a VM migration path; it should not be treated as proof that the application itself has been redesigned or modernized.
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VMs to containers
Migrate to Containers converts VM-based workloads to containers for Google Kubernetes Engine (GKE), GKE Autopilot, GKE Enterprise, or Cloud Run. Documented sources include VMware, AWS, Azure, and Compute Engine VMs. Check the service’s current compatibility guidance for the specific source and workload before selecting this route.
Databases and ongoing replication
Database Migration Service documents source-and-destination combinations for PostgreSQL, MySQL, SQL Server, and Oracle. Datastream provides change data capture and replication for supported database sources and destinations such as BigQuery and Cloud Storage. Engine, version, and direction matter: confirm the exact combination in current service documentation rather than assuming that every database can move through either service.
Rank #2
Bulk data transfer
Storage Transfer Service supports transfers from other cloud providers, online resources, and local data sources. For physical transfer, Google recommends Transfer Appliance for more than 20 TB and up to 1 petabyte, according to Google Cloud documentation accessed in 2026. That range is a recommendation for this product, not a general threshold for deciding how to migrate cloud workloads.
Mainframe and application modernization
Google’s catalog includes a Mainframe Assessment Tool, Dual Run, and Mainframe Connector. On October 5, 2026, Google announced Google Cloud Modernize, bringing together Migration Center, Google Cloud VMware Engine, mainframe modernization, and an EKS-to-GKE migration agent. The announcement describes Modernization Hub as a new in-console experience for analyzing Java, .NET, and mainframe source code and mapping dependencies. Google described the EKS-to-GKE agent as Public Preview in that announcement; confirm its current status before planning around it.
Rank #3
How to distinguish rehosting, replatforming, and refactoring
- Rehost: Move a workload with limited changes, such as migrating a VM to a cloud VM. This can change where it runs without changing how the application is built.
- Replatform: Make targeted changes to run on a different platform—for example, converting a VM-based workload to containers.
- Refactor: Change the application itself to take better advantage of a new architecture. A VM migration tool alone does not perform this work.
These distinctions affect scope, skills, testing, and cutover planning. Google’s Migration Center documentation names all three strategies; AWS describes its tooling as supporting rehosting, refactoring, and modernization. For each workload, decide the target state before treating a migration service as the solution.
How to choose a provider for a specific migration
- Inventory the workload and its dependencies. Establish what runs where, what depends on it, and how the pieces communicate. Compare the providers’ assessment and planning capabilities, not just their transfer tools.
- Check exact source and target compatibility. Identify the hypervisor or cloud, operating system, database engine and version, and target runtime. Google’s documented paths include several cross-cloud sources, but support is tool-specific.
- Set the modernization depth. Decide whether the aim is a VM move, a platform change such as containerization, or application refactoring. The more the target differs from the source, the more validation and application work the plan needs.
- Design data movement and cutover. Compare transfer methods, replication or change-data capture, validation needs, and the acceptable outage or cutover window. AWS identifies data mobility as a separate concern; Google documents database replication and transfer options.
- Plan the landing zone and operating model. Account for identity, governance, compliance, observability, and who will operate the resulting platform. Azure’s migration hub explicitly links to landing-zone and governance guidance; these needs apply to the workload whichever provider is selected.
- Build a workload-specific cost case. Include licensing, data transfer, ongoing operations, and any refactoring—not only the destination compute estimate. The official material reviewed does not establish that one provider is cheapest overall.
What Google Cloud Modernize changes—and what it does not
Google Cloud’s October 5, 2026 announcement gives customers a more unified portfolio label and describes Modernization Hub as an in-console analysis experience. That may make it easier to orient a modernization program around related tools, but it does not turn every migration into one automated process. The announcement’s EKS-to-GKE agent was Public Preview at that time, so its status and suitability require confirmation for a real project.
The same announcement reports 26.57 GiB of RAM per vCPU for the M4N series and claims this can reduce software licensing costs by more than 20% for Oracle and other core-licensed databases. These are Google-published product claims, not independent comparative benchmarks, and they apply to that specific instance and licensing use case—not to cloud migration economics in general.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to verify before committing
- Current regional availability and service status, especially for preview capabilities.
- Compatibility for the exact source platform, operating system, database engine and version, and intended target.
- How replication, validation, rollback, and cutover will work for the workload’s continuity requirements.
- The cost of operating the target environment as well as migrating to it, including licensing and data transfer.
- Whether the team can run the new platform and meet its identity, governance, compliance, and observability requirements.
Official product documentation is useful for defining tool scope, but it is not a substitute for a workload assessment or a comparable performance test. Google lists third-party migration options such as RackWare and notes that its list is a reference, not an endorsement of Google support. Select partners and tools based on verified compatibility and project needs.
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