DatriseAI-first ETL

New York Times to Redash Integration

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

How Datrise loads New York Times into Redash

Datrise syncs New York Times's articles, sections, headlines, bylines, publication dates, and keywords into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How New York Times entities map to Redash

New York Times entityRedash objectNotes
articlesnew_york_times_articlesid PK · custom fields → flattened columns for query results
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 Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the New York Times to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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