Independent comparison for technology buyers. Updated May 2026.
Quick verdict: Choose Databricks for an open Delta lakehouse spanning ETL, ML/AI, and BI on Azure with multi-cloud portability. Choose Azure Synapse Analytics for an Azure-native unified analytics platform with dedicated and serverless SQL pools that may migrate to Microsoft Fabric. The differentiator is multi-cloud lakehouse with strong ML tooling versus an Azure-coupled analytics stack on a Microsoft Fabric path.
| Criteria | Databricks | Azure Synapse Analytics |
|---|---|---|
| Rating | 4.6 / 5.0 (3,200 reviews) | 4.2 / 5.0 (1,600 reviews) |
| Architecture | Lakehouse on Delta / Spark + Photon | Dedicated SQL, serverless SQL, Spark pools |
| Cloud Deployment | AWS, Azure, GCP | Azure only |
| Pricing Model | DBUs + Azure VM/storage | DWU-hour, per-TB scanned, Spark vCore-hour |
| ML / AI | MLflow, Mosaic AI, model serving | Azure ML, Synapse ML |
| BI Integration | Databricks SQL + Power BI | Power BI native, dataflows |
| Open Format | Delta Lake, Iceberg via UniForm | Delta, Parquet on ADLS |
| Future Direction | Mosaic AI, generative AI workloads | Migration path to Microsoft Fabric |
| Best For | ETL, ML/AI, lakehouse on Azure | Azure SQL DW workloads, Fabric direction |
Databricks on Azure (Azure Databricks) is a co-engineered service available through the Azure Portal with Azure-native networking, identity, and billing. It runs the same lakehouse platform — Delta Lake, Photon, Databricks SQL, MLflow, Mosaic AI, Unity Catalog — that exists on AWS and GCP. Workloads include batch ETL, streaming, BI, classic ML, and generative AI.
Azure Synapse Analytics is Microsoft's Azure analytics platform with dedicated SQL pool, serverless SQL pool, Spark pools, and integrated pipelines. Power BI integrates natively. Microsoft's strategic platform going forward is Microsoft Fabric; Synapse remains supported but most new investment is targeted at Fabric, and Synapse workloads have a documented migration path.
On Azure, the strategic comparison often becomes Databricks versus Microsoft Fabric rather than Synapse. See Snowflake vs Fabric and Microsoft Fabric vs Synapse for related context. Compare more options in data analytics.
Databricks on Azure combines DBU charges (Azure SKU) with the underlying Azure VM and storage. Enterprise spend commonly lands $300,000-$10M ARR including Azure infrastructure. Photon and Serverless SQL warehouses carry premium DBU rates; spot or low-priority VMs for ETL jobs are typical optimisations.
Azure Synapse dedicated SQL pool runs around $1.20/hour per 100 DWU on demand, with reserved discounts. Serverless SQL is around $5/TB scanned. Spark pools are billed per vCore-hour. Storage uses standard Azure Data Lake Storage Gen2 rates. Enterprise Synapse spend typically lands $200,000-$6M ARR. Microsoft Enterprise Agreement discounts often shape the comparison meaningfully.
Choose Azure Databricks when ML/AI workloads need first-class tooling alongside ETL and BI, when an open Delta or Iceberg lakehouse is a deliberate direction, when multi-cloud portability across Azure, AWS, and GCP matters, or when generative AI workloads via Mosaic AI are in scope.
Choose Azure Synapse Analytics when existing dedicated SQL pool workloads must continue, when Power BI dependency is high and DirectLake / native semantic models matter, or when migration to Microsoft Fabric is the planned medium-term direction.
This Databricks vs. Synapse comparison summarises the practical differences between the two options for enterprise buyers. The analysis covers pricing models, target customer size, deployment options, integration coverage, and customer-reported strengths. Use the related comparisons below to evaluate either product against other alternatives.