Compare warehouse platforms and workload economics
Compare the platform to the workload, including cases where another architecture fits better.
Relevant capabilities
- Workload and architecture comparison
- Managed open-source data stacks
- Option to run alongside an existing platform
How should you compare the options?
- Separate storage, SQL analytics, streaming, operational queries and machine-learning workloads.
- Check compatibility, data movement and governance before choosing replacement engines.
- Compare migration effort and coexistence options alongside recurring compute and software charges.
What should you bring?
- Workload inventory and representative queries
- Current compute, storage, licensing and support spend
- Data movement, governance and service-level requirements
What does a practical first workflow look like?
- Identify the workloads that create cost or operational pain.
- Choose representative queries and data for a bounded comparison.
- Validate results, performance and migration compatibility.
- Move suitable workloads in stages and retain capabilities that still fit the existing platform.
What should you check before expanding?
- Reconcile query outputs and data completeness.
- Measure workload-level cost and concurrency.
- Test failure recovery and access controls before cutover.
How should you evaluate the cost?
Compare compute, storage, licensing, support and migration effort at the same workload and service level. 0% compute markup does not mean zero platform or operating cost.
What needs checking before switching?
Identify which workloads can move and which capabilities should stay on the current platform. Confirm compatibility before migration.