DatriseAI-first ETL

Retently to Microsoft SQL Server Integration

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

How Datrise loads Retently into Microsoft SQL Server

Datrise syncs Retently's surveys, responses, customers, NPS scores, campaigns, and feedback comments 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

Retently: NPS and customer satisfaction survey tracking.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Retently entities map to Microsoft SQL Server

Retently entityMicrosoft SQL Server objectNotes
surveysretently_surveysid PK · custom fields → NVARCHAR(MAX) JSON columns
responsesretently_responsesid PK · linked to retently_surveys
customersretently_customersid PK · linked to retently_surveys
NPS scoresretently_nps_scoresid PK · linked to retently_surveys

FAQ

How does Datrise handle Retently'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 Retently 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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