DatriseAI-first ETL

New York Times Mode

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

How Datrise loads New York Times into Mode

Datrise syncs New York Times's records, events, and configuration objects into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

New York Times: SaaS or API data source for analytics and warehouse sync.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How New York Times entities map to Mode

New York Times entityMode objectNotes
recordsnew_york_times_recordsid PK · custom fields → flattened columns for SQL and notebooks
eventsnew_york_times_eventstemporal columns events
configuration objectsnew_york_times_configuration_objectsid PK · linked to new_york_times_records

FAQ

How does Datrise handle New York Times's custom fields in Mode?

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

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

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

Related pipelines

Early access

Connect New York Times to Mode the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.