Vtiger → Domo
AI-first ETL from Vtiger into Domo. Governed entities, incremental sync, typed landing tables.
How Datrise loads Vtiger into Domo
Datrise syncs Vtiger's sales, support, and lifecycle workflows in a unified CRM model into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.
Ideal for all-in-one cloud BI with built-in ETL.
Endpoints
Vtiger: Unified CRM for sales, help desk, and customer lifecycle workflows.
Domo: Cloud BI platform combining data integration and executive dashboards.
How Vtiger entities map to Domo
| Vtiger entity | Domo object | Notes |
|---|---|---|
| sales | vtiger_sales | id PK · custom fields → flattened columns for Magic ETL |
| 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 Domo?
Flexible values are stored as flattened columns for Magic ETL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Domo types.
How does the Vtiger to Domo sync stay up to date?
It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.
Related pipelines
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