DatriseAI-first ETL

Source connector

New York Times connector

New York Times integration for databases, warehouses and BI tools

Article archive and top-stories metadata. Datrise captures New York Times entities such as articles, sections, headlines, bylines, publication dates and keywords, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

Of the 6 objects, 6 sync as upserts keyed on the primary key and 0 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `new_york_times_articles`) with a schema derived from the New York Times API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the New York Times pipeline page, and join the waitlist to get the New York Times connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What New York Times data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

ObjectLanding tableSync mode
articlesnew_york_times_articlesUpsert by primary key, incremental on updated-at
sectionsnew_york_times_sectionsUpsert by primary key, incremental on updated-at
headlinesnew_york_times_headlinesUpsert by primary key, incremental on updated-at
bylinesnew_york_times_bylinesUpsert by primary key, incremental on updated-at
publication datesnew_york_times_publication_datesUpsert by primary key, incremental on updated-at
keywordsnew_york_times_keywordsUpsert by primary key, incremental on updated-at

Popular destinations for New York Times

Choose a destination below to open the ready pipeline page.

  • A
    Airtable

    Relational spreadsheet destination for ops and go-to-market teams.

    View pipeline
  • A
    Amazon Athena

    Serverless SQL over S3 data lake tables.

    View pipeline
  • A
    Amazon DynamoDB

    Serverless key-value and document store on AWS.

    View pipeline
  • A
    Amazon QuickSight

    AWS serverless BI with SPICE and embedded analytics.

    View pipeline
  • A
    Amazon Redshift

    AWS petabyte-scale warehouse with Spectrum.

    View pipeline
  • A
    Amazon S3 Data Lake

    Object storage landing zone for parquet and snapshots.

    View pipeline
  • A
    Apache Superset

    Open-source BI for SQL exploration, charts, and dashboard publishing.

    View pipeline
  • A
    Azure Data Lake Storage

    ADLS Gen2 object storage for analytics workloads.

    View pipeline
  • A
    Azure Synapse

    Microsoft analytics workspace with SQL pools.

    View pipeline

New York Times connector FAQ

What New York Times data does the connector extract?
6 objects: articles, sections, headlines, bylines, publication dates and keywords. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the New York Times integration incremental?
Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load New York Times data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each New York Times → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your New York Times pipeline with guided onboarding

Join the waitlist to get priority access for New York Times integrations with guided setup, schema-aware mapping, and production-grade incremental sync.