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 entity | MongoDB object | Notes |
|---|---|---|
| relationship records | nimble_relationship_records | id PK · custom fields → native nested documents |
| deals | nimble_deals | id PK · linked to nimble_relationship_records |
| tasks | nimble_tasks | id PK · linked to nimble_relationship_records |
| activity intelligence | nimble_activity_intelligence | BSON 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.
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