DatriseAI-first ETL

Aftership Microsoft SQL Server

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

How Datrise loads Aftership into Microsoft SQL Server

Datrise syncs Aftership's records, events, and configuration objects 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

Aftership: SaaS or API data source for analytics and warehouse sync.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Aftership entities map to Microsoft SQL Server

Aftership entityMicrosoft SQL Server objectNotes
recordsaftership_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsaftership_eventsdatetime2 events
configuration objectsaftership_configuration_objectsid PK · linked to aftership_records

FAQ

How does Datrise handle Aftership'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 Aftership 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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