Senseforce to MongoDB Integration
AI-first ETL from Senseforce into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Senseforce into MongoDB
Datrise syncs Senseforce's assets, sensor readings, events, machines, time series values, and alarms into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.
Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.
Ideal for document-oriented apps that want CRM data in their existing Mongo store.
Endpoints
Senseforce: Industrial IoT machine telemetry and analytics.
MongoDB: Document database for flexible schemas.
How Senseforce entities map to MongoDB
| Senseforce entity | MongoDB object | Notes |
|---|---|---|
| assets | senseforce_assets | id PK · custom fields → native nested documents |
| sensor readings | senseforce_sensor_readings | id PK · linked to senseforce_assets |
| events | senseforce_events | BSON Date events |
| machines | senseforce_machines | id PK · linked to senseforce_assets |
FAQ
How does Datrise handle Senseforce's custom fields in MongoDB?
Flexible values are stored as native nested documents, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MongoDB types.
How does the Senseforce to MongoDB sync stay up to date?
It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.
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