DatriseAI-first ETL

Salesforce Health Cloud MongoDB

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

How Datrise loads Salesforce Health Cloud into MongoDB

Datrise syncs Salesforce Health Cloud'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

Salesforce Health Cloud: Healthcare CRM for accounts, compliance, and field engagement.

MongoDB: Document database for flexible schemas.

How Salesforce Health Cloud entities map to MongoDB

Salesforce Health Cloud entityMongoDB objectNotes
contactssalesforce_health_cloud_contactsid PK · custom fields → native nested documents
accountssalesforce_health_cloud_accountsid PK · linked to salesforce_health_cloud_contacts
dealssalesforce_health_cloud_dealsid PK · linked to salesforce_health_cloud_contacts
activitiessalesforce_health_cloud_activitiesBSON Date events

FAQ

How does Datrise handle Salesforce Health Cloud'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 Salesforce Health Cloud 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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