DatriseAI-first ETL

Vtiger Microsoft SQL Server

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

How Datrise loads Vtiger into Microsoft SQL Server

Datrise syncs Vtiger's sales, support, and lifecycle workflows in a unified CRM model into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

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

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Vtiger entities map to Microsoft SQL Server

Vtiger entityMicrosoft SQL Server objectNotes
salesvtiger_salesid PK · custom fields → NVARCHAR(MAX) JSON columns
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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Vtiger to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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