DatriseAI-first ETL

Segment Microsoft SQL Server

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

How Datrise loads Segment into Microsoft SQL Server

Datrise syncs Segment's sources, destinations, track events, identify calls, and schema catalog 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

Segment: Customer data platform routing events to warehouses.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Segment entities map to Microsoft SQL Server

Segment entityMicrosoft SQL Server objectNotes
sourcessegment_sourcesid PK · custom fields → NVARCHAR(MAX) JSON columns
destinationssegment_destinationsid PK · linked to segment_sources
track eventssegment_track_eventsdatetime2 events
identify callssegment_identify_callsid PK · linked to segment_sources

FAQ

How does Datrise handle Segment'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 Segment 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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