DatriseAI-first ETL

Vtiger Spotfire

AI-first ETL from Vtiger into Spotfire. Governed entities, incremental sync, typed landing tables.

How Datrise loads Vtiger into Spotfire

Datrise syncs Vtiger's sales, support, and lifecycle workflows in a unified CRM model into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Vtiger: Unified CRM for sales, help desk, and customer lifecycle workflows.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Vtiger entities map to Spotfire

Vtiger entitySpotfire objectNotes
salesvtiger_salesid PK · custom fields → flattened columns for visualizations
supportvtiger_supportid PK · linked to vtiger_sales
lifecycle workflows in a unified CRM modelvtiger_lifecycle_workflows_in_a_unified_crm_modelid PK · linked to vtiger_sales

FAQ

How does Datrise handle Vtiger's custom fields in Spotfire?

Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.

How does the Vtiger to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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