Senseforce to Microsoft SQL Server Integration

How Datrise loads Senseforce into Microsoft SQL Server

Datrise syncs Senseforce's assets, sensor readings, events, machines, time series values, and alarms into Microsoft SQL Server 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 a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Senseforce: Industrial IoT machine telemetry and analytics.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Senseforce entities map to Microsoft SQL Server

Senseforce entity	Microsoft SQL Server 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 Microsoft SQL Server?

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 Microsoft SQL Server types.

How does the Senseforce to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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