Nutshell → MongoDB
AI-first ETL from Nutshell into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nutshell into MongoDB
Datrise syncs Nutshell's pipeline records, activity history, and conversion-focused sales metrics 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
Nutshell: Sales CRM for teams that need simple reporting and pipeline velocity.
MongoDB: Document database for flexible schemas.
How Nutshell entities map to MongoDB
| Nutshell entity | MongoDB object | Notes |
|---|---|---|
| pipeline records | nutshell_pipeline_records | id PK · custom fields → native nested documents |
| activity history | nutshell_activity_history | BSON Date events |
| conversion-focused sales metrics | nutshell_conversion_focused_sales_metrics | id PK · linked to nutshell_pipeline_records |
FAQ
How does Datrise handle Nutshell'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 Nutshell 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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