DatriseAI-first ETL

Codat to Chartio Integration

AI-first ETL from Codat into Chartio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Codat into Chartio

Datrise syncs Codat's companies, accounts, invoices, bills, journal entries, and payments 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

Codat: Unified API for accounting and banking data.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Codat entities map to Chartio

Codat entityChartio objectNotes
companiescodat_companiesid PK · custom fields → flattened columns for visual SQL
accountscodat_accountsid PK · linked to codat_companies
invoicescodat_invoicesid PK · linked to codat_companies
billscodat_billsid PK · linked to codat_companies

FAQ

How does Datrise handle Codat'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 Codat to Chartio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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