DatriseAI-first ETL

Aftership to Microsoft SQL Server Integration

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 shipments, trackings, checkpoints, couriers, delivery statuses, and notifications 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: Shipment tracking and delivery notifications.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Aftership entities map to Microsoft SQL Server

Aftership entityMicrosoft SQL Server objectNotes
shipmentsaftership_shipmentsid PK · custom fields → NVARCHAR(MAX) JSON columns
trackingsaftership_trackingsid PK · linked to aftership_shipments
checkpointsaftership_checkpointsid PK · linked to aftership_shipments
couriersaftership_couriersid PK · linked to aftership_shipments

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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