Kommo → Chartio
AI-first ETL from Kommo into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Kommo into Chartio
Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.
Ideal for drag-and-drop charting over a database.
Endpoints
Kommo: Conversational CRM for WhatsApp, chat funnels, and sales automation.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Kommo entities map to Chartio
| Kommo entity | Chartio object | Notes |
|---|---|---|
| conversational CRM events | kommo_conversational_crm_events | temporal columns 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 Chartio?
Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.
How does the Kommo to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Kommo
Early access
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