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 entity | Spotfire object | Notes |
|---|---|---|
| sales | vtiger_sales | id PK · custom fields → flattened columns for visualizations |
| support | vtiger_support | id PK · linked to vtiger_sales |
| lifecycle workflows in a unified CRM model | vtiger_lifecycle_workflows_in_a_unified_crm_model | id 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.
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