DatriseAI-first ETL

Zendesk MongoDB

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

How Datrise loads Zendesk into MongoDB

Datrise syncs Zendesk's tickets, users, organizations, macros, and satisfaction ratings 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

Zendesk: Customer support suite with tickets and knowledge base.

MongoDB: Document database for flexible schemas.

How Zendesk entities map to MongoDB

Zendesk entityMongoDB objectNotes
ticketszendesk_ticketsid PK · custom fields → native nested documents
userszendesk_usersid PK · linked to zendesk_tickets
organizationszendesk_organizationsid PK · linked to zendesk_tickets
macroszendesk_macrosid PK · linked to zendesk_tickets

FAQ

How does Datrise handle Zendesk'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 Zendesk 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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