π Azure Synapse Link for Dataverse vs Dataverse Long-Term Retention (LTR)
Feature | Azure Synapse Link for Dataverse | Dataverse Long-Term Retention (LTR) |
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π― Purpose | For near real-time analytics and reporting. | For archiving inactive data to reduce storage costs. |
π️ Where Data Goes | Copies Dataverse data into Azure Synapse Analytics or Azure Data Lake for analysis. | Moves inactive Dataverse records to a cold storage tier inside Dataverse itself. |
π Use Case | Power BI reports, advanced analytics, AI/ML scenarios. | Keep historical records (e.g., old cases, orders) accessible but off active storage. |
π♂️ Performance Impact | Minimal; works with change tracking for incremental updates. | Improves performance of Dataverse by cleaning up active tables. |
π° Cost Consideration | Azure costs for storage/compute (Synapse/Data Lake). | Lower Dataverse storage costs (cold tier = cheaper). |
⚡ Access to Archived Data | Direct access via Synapse or Data Lake (external). | Archived data is read-only and not directly editable. |
π Data Update Frequency | Near real-time (supports incremental data refresh). | Periodic (retention policies run on schedule, e.g., daily). |
π¨π» Developer/Business Use | Enables advanced analytics, AI models, dashboards. | For admin-level data management and storage optimization. |
π ️ Configuration Effort | Moderate (Synapse Link setup + Power BI/Azure config). | Low (retention policies defined in Power Platform Admin). |
π Licensing | Requires Azure subscription (Synapse, Data Lake, Power BI). | Included with Dataverse – no extra license. |
What Azure Synapse Link for Dataverse does
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Connects Dataverse tables to Azure Synapse or Data Lake Gen2.
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Streams data almost in real-time.
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Use cases:
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Build Power BI dashboards over large datasets.
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Run AI/ML models with Azure Machine Learning.
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Analyze historical and transactional data (e.g., millions of orders).
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⚡ Keeps operational systems (like Dynamics CE) lightweight since heavy queries run in Synapse.
π️ What Dataverse Long-Term Retention does
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Moves inactive records (e.g., closed cases older than 3 years) into cold storage.
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Frees up Dataverse primary storage capacity and reduces licensing/storage costs.
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Archived records:
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Are read-only.
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Can’t be edited but can still be viewed (via API or model-driven apps).
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Must be restored (moved back) to active storage for editing.
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π¦ When to Use Which?
Scenario | Use Azure Synapse Link? | Use LTR? |
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Build reports over millions of transactions | ✅ | ❌ |
Archive closed opportunities older than 5 years | ❌ | ✅ |
Run machine learning on customer sentiment data | ✅ | ❌ |
Free up Dataverse primary storage from old records | ❌ | ✅ |
Compliance storage for inactive case data | ❌ | ✅ |
Key Takeaways
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Synapse Link = Export for analytics.
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LTR = Archive for storage optimization.
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They can work together:
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Use LTR to clean up Dataverse active tables.
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Use Synapse Link to run analytics on both active and archived data (if exported to Data Lake).
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