Smaily to Chartio Integration
AI-first ETL from Smaily into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Smaily into Chartio
Datrise syncs Smaily's subscribers, campaigns, lists, autoresponders, email events, and segments 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
Smaily: Email and SMS campaigns with subscriber segments.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Smaily entities map to Chartio
| Smaily entity | Chartio object | Notes |
|---|---|---|
| subscribers | smaily_subscribers | id PK · custom fields → flattened columns for visual SQL |
| campaigns | smaily_campaigns | id PK · linked to smaily_subscribers |
| lists | smaily_lists | id PK · linked to smaily_subscribers |
| autoresponders | smaily_autoresponders | id PK · linked to smaily_subscribers |
FAQ
How does Datrise handle Smaily'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 Smaily to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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Early access
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