Salesloft → MongoDB
AI-first ETL from Salesloft into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Salesloft into MongoDB
Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution 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
Salesloft: Revenue workflow platform for cadences, conversations, and coaching signals.
MongoDB: Document database for flexible schemas.
How Salesloft entities map to MongoDB
| Salesloft entity | MongoDB object | Notes |
|---|---|---|
| cadence activity | salesloft_cadence_activity | BSON Date events |
| conversation signals | salesloft_conversation_signals | id PK · linked to salesloft_cadence_activity |
| revenue workflow execution | salesloft_revenue_workflow_execution | id PK · linked to salesloft_cadence_activity |
FAQ
How does Datrise handle Salesloft'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 Salesloft 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
More destinations for Salesloft
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