Based on your described setup (daily CSV loads from multiple locations, D365 Synapse Link extraction, 200 GB DWH, and ETL using ADF), here’s a high-level cost comparison between Azure Synapse Analytics and Microsoft Fabric:
Azure Synapse Analytics
- Compute (Dedicated SQL Pool): For a 200 GB warehouse, you'd likely need at least 100 DWUs - which would cost around $900/month if kept running continuously.
- ADF Pipelines: Light ETL jobs like daily file loads and transformation typically cost around $50–100/month depending on frequency and complexity.
- Storage (Hot + Archive): 200 GB hot + ~42 GB archive (1 month retention) might cost ~$5–10/month.
Estimated total: ~$950–1,100/month, depending on DWU size and usage pattern.
Microsoft Fabric
Capacity-based model: Starts at ~$262/month for the base F64 SKU, which gives you:
- Integrated Lakehouse and Warehouse
- Built-in pipelines (no ADF needed separately)
- Native D365 integration (via Synapse Link)
- Storage included (up to 100 TB pooled)
Estimated total: ~$262/month, unless higher compute capacity or concurrency is required.
Differences b/w:
Criteria | Azure Synapse Analytics | Microsoft Fabric |
---|---|---|
Billing Model | Consumption-based (DWU, ADF activity, storage) | Capacity-based (SKU pricing, pooled usage) |
Billing Model | Consumption-based (DWU, ADF activity, storage) | Capacity-based (SKU pricing, pooled usage) |
ETL Tooling | ADF or Synapse pipelines | Built-in Fabric Pipelines |
Ease of D365 Integration | Requires Synapse Link setup | Native integration in Fabric |
Storage Cost | Metered separately | Included in capacity |
User Access (BI) | Requires linking to Power BI Premium | Native Power BI experience |
Best Fit | High-performance analytics, large DWH loads | Unified low-maintenance analytics workflows |
Synapse Analytics gives you more granular control and may suit more complex or high-performance workloads - but comes at a higher cost.
Microsoft Fabric is better suited for streamlined analytics, especially when working with D365 and Power BI, and offers better cost predictability.
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