DatriseAI-first ETL

Zoom MongoDB

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

How Datrise loads Zoom into MongoDB

Datrise syncs Zoom's meetings, participants, webinars, recordings, and usage reports 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

Zoom: Video meetings, webinars, and workplace collaboration.

MongoDB: Document database for flexible schemas.

How Zoom entities map to MongoDB

Zoom entityMongoDB objectNotes
meetingszoom_meetingsid PK · custom fields → native nested documents
participantszoom_participantsid PK · linked to zoom_meetings
webinarszoom_webinarsid PK · linked to zoom_meetings
recordingszoom_recordingsid PK · linked to zoom_meetings

FAQ

How does Datrise handle Zoom'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 Zoom 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

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