Kommo → MongoDB
AI-first ETL from Kommo into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Kommo into MongoDB
Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers 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
Kommo: Conversational CRM for WhatsApp, chat funnels, and sales automation.
MongoDB: Document database for flexible schemas.
How Kommo entities map to MongoDB
| Kommo entity | MongoDB object | Notes |
|---|---|---|
| conversational CRM events | kommo_conversational_crm_events | BSON Date events |
| chats | kommo_chats | id PK · linked to kommo_conversational_crm_events |
| leads | kommo_leads | id PK · linked to kommo_conversational_crm_events |
| sales automation triggers | kommo_sales_automation_triggers | id PK · linked to kommo_conversational_crm_events |
FAQ
How does Datrise handle Kommo'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 Kommo 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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