DatriseAI-first ETL

Onfleet to MongoDB Integration

AI-first ETL from Onfleet into MongoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Onfleet into MongoDB

Datrise syncs Onfleet's tasks, workers, teams, destinations, delivery events, and recipients 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

Onfleet: Last-mile delivery dispatch and driver tracking.

MongoDB: Document database for flexible schemas.

How Onfleet entities map to MongoDB

Onfleet entityMongoDB objectNotes
tasksonfleet_tasksid PK · custom fields → native nested documents
workersonfleet_workersid PK · linked to onfleet_tasks
teamsonfleet_teamsid PK · linked to onfleet_tasks
destinationsonfleet_destinationsid PK · linked to onfleet_tasks

FAQ

How does Datrise handle Onfleet'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 Onfleet to MongoDB sync stay up to date?

It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.

Related pipelines

Early access

Connect Onfleet to MongoDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.