Senseforce to Azure Synapse Integration
AI-first ETL from Senseforce into Azure Synapse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Senseforce into Azure Synapse
Datrise syncs Senseforce's assets, sensor readings, events, machines, time series values, and alarms into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.
Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.
Ideal for Azure analytics estates feeding Power BI.
Endpoints
Senseforce: Industrial IoT machine telemetry and analytics.
Azure Synapse: Microsoft analytics workspace with SQL pools.
How Senseforce entities map to Azure Synapse
| Senseforce entity | Azure Synapse object | Notes |
|---|---|---|
| assets | senseforce_assets | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| sensor readings | senseforce_sensor_readings | id PK · linked to senseforce_assets |
| events | senseforce_events | datetime2 events |
| machines | senseforce_machines | id PK · linked to senseforce_assets |
FAQ
How does Datrise handle Senseforce's custom fields in Azure Synapse?
Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Synapse types.
How does the Senseforce to Azure Synapse sync stay up to date?
It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.
Related pipelines
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