DatriseAI-first ETL

Convex to Chartio Integration

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

How Datrise loads Convex into Chartio

Datrise syncs Convex's documents, tables, functions, indexes, mutations, and queries 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

Convex: Reactive backend with a document database.

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

How Convex entities map to Chartio

Convex entityChartio objectNotes
documentsconvex_documentsid PK · custom fields → flattened columns for visual SQL
tablesconvex_tablesid PK · linked to convex_documents
functionsconvex_functionsid PK · linked to convex_documents
indexesconvex_indexesid PK · linked to convex_documents

FAQ

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

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

Related pipelines

Early access

Connect Convex to Chartio the easy way

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