New York Times connector

Set up the New York Times connector in Kaivo: authentication, configuration, the 4 BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated About 3 hours ago

Kaivo is a fully managed data platform that syncs your New York Times data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from New York Times instead of moving it.

What is the New York Times connector

Sync New York Times articles and most-popular lists into BigQuery with Kaivo to analyse coverage and track what readers engage with.

CategoryOther
StatusGenerally available
AuthenticationAPI key
SetupSelf-service

Getting started with the New York Times connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your New York Times account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating New York Times

Authenticate with your API Key.

FieldDescription
API Key

Your New York Times API key.

Configuring the New York Times connector

When you set up the connector, you provide:

FieldDescription
Start Date

Any data before this date will not be fetched.

End Date

Any data after this date will not be fetched.

Period

Period of time in days for Most Popular streams.

Share Type

Share type for the Most Popular Shared stream.

Tables and columns synced from New York Times

Kaivo syncs 4 tables from New York Times into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

How the New York Times sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where New York Times supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for New York Times?

It depends on how much history is in your New York Times account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when New York Times's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in New York Times, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in New York Times instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the New York Times connector in Kaivo and all of its synced data is deleted with it.

Common use cases for New York Times data

Coverage analysis

Use archive to study article volume by section and keyword over time.

Popularity tracking

Compare most_popular_viewed, shared, and emailed to see what resonates.

Group articles by section to follow topic coverage.

Content archive

Bring articles into BigQuery to build a searchable record.

Use New York Times data in your AI and BI tools

Once New York Times data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with New York Times data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide β†’

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide β†’

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide β†’

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide β†’

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide β†’

Excel

Connect via Power Query's BigQuery connector. Setup guide β†’

Metabase

Open-source BI tool with strong BigQuery support. Setup guide β†’

See our pricing page for New York Times connector pricing and plan details.