DatriseAI-first ETL

Agendor MongoDB

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

How Datrise loads Agendor into MongoDB

Datrise syncs Agendor's contacts, accounts, deals, activities, and lifecycle events 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

Agendor: CRM widely used in Latin America for sales pipeline and customer ops.

MongoDB: Document database for flexible schemas.

How Agendor entities map to MongoDB

Agendor entityMongoDB objectNotes
contactsagendor_contactsid PK · custom fields → native nested documents
accountsagendor_accountsid PK · linked to agendor_contacts
dealsagendor_dealsid PK · linked to agendor_contacts
activitiesagendor_activitiesBSON Date events

FAQ

How does Datrise handle Agendor'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 Agendor 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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