Veeva CRM → Microsoft SQL Server
AI-first ETL from Veeva CRM into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Veeva CRM into Microsoft SQL Server
Datrise syncs Veeva CRM's contacts, accounts, deals, activities, and lifecycle events 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
Veeva CRM: Healthcare CRM for accounts, compliance, and field engagement.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Veeva CRM entities map to Microsoft SQL Server
| Veeva CRM entity | Microsoft SQL Server object | Notes |
|---|---|---|
| contacts | veeva_contacts | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| accounts | veeva_accounts | id PK · linked to veeva_contacts |
| deals | veeva_deals | id PK · linked to veeva_contacts |
| activities | veeva_activities | datetime2 events |
FAQ
How does Datrise handle Veeva CRM'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 Veeva CRM to Microsoft SQL Server sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.
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Early access
Connect Veeva CRM to Microsoft SQL Server the easy way
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