DatriseAI-first ETL

Shopify Byoa Microsoft SQL Server

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

How Datrise loads Shopify Byoa into Microsoft SQL Server

Datrise syncs Shopify Byoa'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

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

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Shopify Byoa entities map to Microsoft SQL Server

Shopify Byoa entityMicrosoft SQL Server objectNotes
recordsshopify_byoa_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsshopify_byoa_eventsdatetime2 events
configuration objectsshopify_byoa_configuration_objectsid PK · linked to shopify_byoa_records

FAQ

How does Datrise handle Shopify Byoa'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 Shopify Byoa 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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