Apollo → MongoDB
AI-first ETL from Apollo into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into MongoDB
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity 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
Apollo: Sales intelligence and engagement platform with account-level activity.
MongoDB: Document database for flexible schemas.
How Apollo entities map to MongoDB
| Apollo entity | MongoDB object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → native nested documents |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | BSON Date events |
FAQ
How does Datrise handle Apollo'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 Apollo 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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