DatriseAI-first ETL

Square Microsoft SQL Server

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

How Datrise loads Square into Microsoft SQL Server

Datrise syncs Square's payments, orders, customers, catalog items, and locations 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

Square: Payments and commerce platform for retail and online sellers.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Square entities map to Microsoft SQL Server

Square entityMicrosoft SQL Server objectNotes
paymentssquare_paymentsid PK · custom fields → NVARCHAR(MAX) JSON columns
orderssquare_ordersid PK · linked to square_payments
customerssquare_customersid PK · linked to square_payments
catalog itemssquare_catalog_itemsid PK · linked to square_payments

FAQ

How does Datrise handle Square'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 Square to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

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