DatriseAI-first ETL

ServiceTitan Chartio

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

How Datrise loads ServiceTitan into Chartio

Datrise syncs ServiceTitan'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

ServiceTitan: Field service CRM for scheduling, jobs, and customer history.

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

How ServiceTitan entities map to Chartio

ServiceTitan entityChartio objectNotes
contactsservicetitan_contactsid PK · custom fields → flattened columns for visual SQL
accountsservicetitan_accountsid PK · linked to servicetitan_contacts
dealsservicetitan_dealsid PK · linked to servicetitan_contacts
activitiesservicetitan_activitiestemporal columns events

FAQ

How does Datrise handle ServiceTitan'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 ServiceTitan 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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