DatriseAI-first ETL

New York Times Google BigQuery

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

How Datrise loads New York Times into Google BigQuery

Datrise syncs New York Times's records, events, and configuration objects into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.

Ideal for Google-stack analytics and ML on serverless infrastructure.

Endpoints

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

Google BigQuery: Serverless analytics warehouse on GCP.

How New York Times entities map to Google BigQuery

New York Times entityGoogle BigQuery objectNotes
recordsnew_york_times_recordsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
eventsnew_york_times_eventsTIMESTAMP 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 Google BigQuery?

Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.

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

It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.

Related pipelines

Early access

Connect New York Times to Google BigQuery 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.