DatriseAI-first ETL

Partnerstack to Chartio Integration

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

How Datrise loads Partnerstack into Chartio

Datrise syncs Partnerstack's partners, customers, transactions, rewards, links, and group memberships 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

Partnerstack: Partner, affiliate, and reseller program management.

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

How Partnerstack entities map to Chartio

Partnerstack entityChartio objectNotes
partnerspartnerstack_partnersid PK · custom fields → flattened columns for visual SQL
customerspartnerstack_customersid PK · linked to partnerstack_partners
transactionspartnerstack_transactionsid PK · linked to partnerstack_partners
rewardspartnerstack_rewardsid PK · linked to partnerstack_partners

FAQ

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

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

Related pipelines

Early access

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