DatriseAI-first ETL

My Hours MongoDB

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

How Datrise loads My Hours into MongoDB

Datrise syncs My Hours's records, events, and configuration objects 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

My Hours: SaaS or API data source for analytics and warehouse sync.

MongoDB: Document database for flexible schemas.

How My Hours entities map to MongoDB

My Hours entityMongoDB objectNotes
recordsmy_hours_recordsid PK · custom fields → native nested documents
eventsmy_hours_eventsBSON Date events
configuration objectsmy_hours_configuration_objectsid PK · linked to my_hours_records

FAQ

How does Datrise handle My Hours'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 My Hours 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

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