Public API to Chartio Integration
AI-first ETL from Public API into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Public API into Chartio
Datrise syncs Public API's records, response payloads, pagination cursors, request parameters, schemas, and fetch timestamps 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
Public API: Generic REST endpoint pulled on a schedule.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Public API entities map to Chartio
| Public API entity | Chartio object | Notes |
|---|---|---|
| records | public_api_records | id PK · custom fields → flattened columns for visual SQL |
| response payloads | public_api_response_payloads | id PK · linked to public_api_records |
| pagination cursors | public_api_pagination_cursors | id PK · linked to public_api_records |
| request parameters | public_api_request_parameters | id PK · linked to public_api_records |
FAQ
How does Datrise handle Public API'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 Public API to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Public API
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