DatriseAI-first ETL

Datascope to Microsoft SQL Server Integration

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

How Datrise loads Datascope into Microsoft SQL Server

Datrise syncs Datascope's forms, submissions, users, locations, attachments, and answers 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

Datascope: Mobile forms for field data capture.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Datascope entities map to Microsoft SQL Server

Datascope entityMicrosoft SQL Server objectNotes
formsdatascope_formsid PK · custom fields → NVARCHAR(MAX) JSON columns
submissionsdatascope_submissionsid PK · linked to datascope_forms
usersdatascope_usersid PK · linked to datascope_forms
locationsdatascope_locationsid PK · linked to datascope_forms

FAQ

How does Datrise handle Datascope'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 Datascope 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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