DatriseAI-first ETL

Impact to Microsoft SQL Server Integration

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

How Datrise loads Impact into Microsoft SQL Server

Datrise syncs Impact's partners, actions, clicks, conversions, payouts, and campaigns 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

Impact: Partnership and affiliate performance tracking.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Impact entities map to Microsoft SQL Server

Impact entityMicrosoft SQL Server objectNotes
partnersimpact_partnersid PK · custom fields → NVARCHAR(MAX) JSON columns
actionsimpact_actionsid PK · linked to impact_partners
clicksimpact_clicksid PK · linked to impact_partners
conversionsimpact_conversionsid PK · linked to impact_partners

FAQ

How does Datrise handle Impact'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 Impact 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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