DatriseAI-first ETL

New York Times to ClickHouse Integration

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

How Datrise loads New York Times into ClickHouse

Datrise syncs New York Times's articles, sections, headlines, bylines, publication dates, and keywords into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

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

ClickHouse: Columnar OLAP engine for fast aggregations.

How New York Times entities map to ClickHouse

New York Times entityClickHouse objectNotes
articlesnew_york_times_articlesid PK · custom fields → JSON or Map 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 ClickHouse?

Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.

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

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

Early access

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