DatriseAI-first ETL

Nimble MongoDB

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

How Datrise loads Nimble into MongoDB

Datrise syncs Nimble's relationship records, deals, tasks, and activity intelligence 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

Nimble: Relationship-focused CRM for SMB sales teams.

MongoDB: Document database for flexible schemas.

How Nimble entities map to MongoDB

Nimble entityMongoDB objectNotes
relationship recordsnimble_relationship_recordsid PK · custom fields → native nested documents
dealsnimble_dealsid PK · linked to nimble_relationship_records
tasksnimble_tasksid PK · linked to nimble_relationship_records
activity intelligencenimble_activity_intelligenceBSON Date events

FAQ

How does Datrise handle Nimble'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 Nimble 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

Connect Nimble to MongoDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.