EspoCRM → Chartio
AI-first ETL from EspoCRM into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads EspoCRM into Chartio
Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation events 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
EspoCRM: Open-source CRM for pipeline management and custom entity modeling.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How EspoCRM entities map to Chartio
| EspoCRM entity | Chartio object | Notes |
|---|---|---|
| pipeline entities | espocrm_pipeline_entities | id PK · custom fields → flattened columns for visual SQL |
| custom objects | espocrm_custom_objects | id PK · linked to espocrm_pipeline_entities |
| process automation events | espocrm_process_automation_events | temporal columns events |
FAQ
How does Datrise handle EspoCRM'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 EspoCRM to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for EspoCRM
Early access
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