DatriseAI-first ETL

Datascope to MongoDB Integration

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

How Datrise loads Datascope into MongoDB

Datrise syncs Datascope's forms, submissions, users, locations, attachments, and answers 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

Datascope: Mobile forms for field data capture.

MongoDB: Document database for flexible schemas.

How Datascope entities map to MongoDB

Datascope entityMongoDB objectNotes
formsdatascope_formsid PK · custom fields → native nested documents
submissionsdatascope_submissionsid PK · linked to datascope_forms
usersdatascope_usersid PK · linked to datascope_forms
locationsdatascope_locationsid PK · linked to datascope_forms

FAQ

How does Datrise handle Datascope'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 Datascope 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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