Databricks is the same platform on every cloud: Delta Lake, Unity Catalog, MLflow, Databricks SQL, and the notebook experience are identical, and code developed on one cloud runs on another with only configuration changes. The meaningful differences are the cloud underneath: compute pricing and variety, the surrounding service ecosystem, procurement, and which provider operates the platform.
This page compares Databricks on AWS and Azure Databricks on the dimensions that matter most when choosing a foundation. If you are already on Azure Databricks and considering a move, see our Azure to AWS migration services.
Cost
Compute is the dominant line item in any Databricks deployment, and AWS offers more ways to reduce it:
| Lever | AWS | Azure |
|---|---|---|
| Spare-capacity pricing | EC2 Spot, up to 90% off On-Demand | Azure Spot VMs, similar discounts, smaller capacity pool |
| ARM-based compute | AWS Graviton (up to 3x better price performance for Databricks) | Not available |
| Committed spend | Databricks via AWS Marketplace draws down AWS commitments | Azure consumption commitments via MCA/EAs |
| Instance variety | Widest EC2 selection: memory, storage, GPU, custom silicon | Narrower D-series/E-series selection |
Organizations that have replatformed analytics workloads from Azure to Databricks on AWS have reported infrastructure cost reductions of around 40%.
Platform operation
- AWS: Databricks is operated directly by Databricks. AWS was the first cloud Databricks launched on, and new platform capabilities reach general availability on AWS first.
- Azure: Azure Databricks is a first-party Microsoft service, co-engineered with Databricks and sold through the Azure portal. It integrates deeply with Entra ID, Power BI, and the rest of the Microsoft estate, but feature availability typically trails AWS.
Ecosystem
| Capability | AWS | Azure |
|---|---|---|
| Lakehouse storage | Amazon S3, the de-facto lakehouse standard | ADLS Gen2 |
| Streaming | Kinesis, MSK | Event Hubs |
| AI inference | Amazon Bedrock, pay-per-token, many providers | Azure OpenAI / AI Foundry |
| Warehousing & federation | Redshift, Athena, Glue | Microsoft Fabric, Synapse |
| Identity | IAM roles + any enterprise IdP via SSO/SCIM | Deep native Entra ID integration |
Which should you choose?
Stay on Azure Databricks if your organization is standardized on the Microsoft estate (Entra ID, Power BI, Fabric, Azure procurement) and the integration friction of moving outweighs the compute savings.
Choose Databricks on AWS if compute cost is a top concern, your data already lands in S3, you want the fastest access to new Databricks features, or your AI roadmap needs the inference economics of Amazon Bedrock.
Already on Azure Databricks? We help teams migrate to AWS with a phased approach that keeps production workloads running.
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