Keap → Chartio
AI-first ETL from Keap into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Keap into Chartio
Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows 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
Keap: SMB CRM with pipeline automation, email, and appointment flows.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Keap entities map to Chartio
| Keap entity | Chartio object | Notes |
|---|---|---|
| SMB contacts | keap_smb_contacts | id PK · custom fields → flattened columns for visual SQL |
| opportunities | keap_opportunities | id PK · linked to keap_smb_contacts |
| automations | keap_automations | id PK · linked to keap_smb_contacts |
| appointment workflows | keap_appointment_workflows | id PK · linked to keap_smb_contacts |
FAQ
How does Datrise handle Keap'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 Keap to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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