Vincle → Microsoft SQL Server
AI-first ETL from Vincle into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Vincle into Microsoft SQL Server
Datrise syncs Vincle'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
Vincle: European CRM for SMB and mid-market sales teams.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Vincle entities map to Microsoft SQL Server
| Vincle entity | Microsoft SQL Server object | Notes |
|---|---|---|
| contacts | vincle_contacts | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| accounts | vincle_accounts | id PK · linked to vincle_contacts |
| deals | vincle_deals | id PK · linked to vincle_contacts |
| activities | vincle_activities | datetime2 events |
FAQ
How does Datrise handle Vincle'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 Vincle 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
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