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