DatriseAI-first ETL

Senseforce to PostgreSQL Integration

AI-first ETL from Senseforce into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Senseforce into PostgreSQL

Datrise syncs Senseforce's assets, sensor readings, events, machines, time series values, and alarms into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Senseforce: Industrial IoT machine telemetry and analytics.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Senseforce entities map to PostgreSQL

Senseforce entityPostgreSQL objectNotes
assetssenseforce_assetsid PK · custom fields → jsonb columns
sensor readingssenseforce_sensor_readingsid PK · linked to senseforce_assets
eventssenseforce_eventstimestamptz events
machinessenseforce_machinesid PK · linked to senseforce_assets

FAQ

How does Datrise handle Senseforce's custom fields in PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Senseforce to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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