DatriseAI-first ETL

New York Times to Microsoft SQL Server Integration

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

How Datrise loads New York Times into Microsoft SQL Server

Datrise syncs New York Times's articles, sections, headlines, bylines, publication dates, and keywords 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

New York Times: Article archive and top-stories metadata.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How New York Times entities map to Microsoft SQL Server

New York Times entityMicrosoft SQL Server objectNotes
articlesnew_york_times_articlesid PK · custom fields → NVARCHAR(MAX) JSON columns
sectionsnew_york_times_sectionsid PK · linked to new_york_times_articles
headlinesnew_york_times_headlinesid PK · linked to new_york_times_articles
bylinesnew_york_times_bylinesid PK · linked to new_york_times_articles

FAQ

How does Datrise handle New York Times'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 New York Times 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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