DatriseAI-first ETL

Propertybase Chartio

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

How Datrise loads Propertybase into Chartio

Datrise syncs Propertybase's contacts, accounts, deals, activities, and lifecycle events 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

Propertybase: Real estate CRM for leads, listings, and agent follow-up.

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

How Propertybase entities map to Chartio

Propertybase entityChartio objectNotes
contactspropertybase_contactsid PK · custom fields → flattened columns for visual SQL
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiestemporal columns events

FAQ

How does Datrise handle Propertybase'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 Propertybase 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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