Sync from New York Times to Google PubSub

with open data movement

Extract and load (ELT) your New York Times data into Google PubSub in minutes with our open-source data integration connector.

Eliminate the time you spend on building and maintaining your data pipelines by integrating your data with Airbyte instead.
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Start syncing data from New York Times to Google PubSub in three easy steps

1

Setup a New York Times connector in Airbyte

Connect to New York Times or one of 400 Airbyte data sources through simple account authentication

2

Set up Google PubSub as the destination connector

Connect to Google PubSub or one of 50+ Airbyte data destinations through simple account authentication

3

Sync your Data

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in Google PubSub you want that data to be loaded.

LOVED by 10,000 (DATA) ENGINEERS

Ship more quickly with the only solution that fits ALL your needs.

As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines

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Airbyte’s catalog of 300+ pre-built, no-code connectors is the largest in the industry and is doubling every year, thanks to its open-source community, while closed-source catalogs have plateaued.

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Build custom connectors in 10 min with our Connector Development Kit (CDK), and get them maintained by us or our community. Add them to Airbyte to enable your whole team to leverage them.
Customize ANY Airbyte connectors to address Your custom needs. Our connector’s code is open-source, so you can edit it as you see fit.

Reliability at every level

Airbyte ensure your team’s time is no longer time spent on maintenance with our reliability SLAs on our GA connectors.
Airbyte will also give you visibility and control of your data freshness at the stream level for all your connections.

It’s never been easier to integrate your New York Times data into Google PubSub

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is New York Times?

The Times Developer Network is our API clearinghouse and community. You need to read the API documentation and browse the application gallery to get the latest news about the New York Times API. If you do not agree to any of the terms below or the NYT Terms of Service, NYT does not grant you a license to use the NYT API. In the event of any inconsistency between these Terms of Use and the Terms of Service, these Terms of Use control.

What is Google PubSub?

Google Pub/Sub is an asynchronous messaging service built to be both highly reliable and scalable. Based on a component of Google’s infrastructure, Pub/Sub offers the capabililty of sending more than 500 million messages (over 1 TB of data) per second.

What data can you extract from New York Times?

The New York Times API provides access to a wide range of data categories, including:  

1. Articles: Full-text articles from the New York Times, including news, opinion, and feature pieces.  
2. Multimedia: Images, videos, and other multimedia content from the New York Times.  
3. Best Sellers: Lists of best-selling books, both fiction and non-fiction, as compiled by the New York Times.  
4. Movie Reviews: Reviews of movies from the New York Times, including ratings and summaries.  
5. TimesTags: A comprehensive list of tags used by the New York Times to categorize articles and other content.  
6. Times Newswire: A real-time feed of breaking news stories from the New York Times.  
7. Top Stories: A list of the most popular articles on the New York Times website, updated in real-time.  
8. Archive: Access to the New York Times archive, including articles dating back to 1851.  
9. Times Insider: Exclusive content from the New York Times, including behind-the-scenes stories and interviews with journalists.  

Overall, the New York Times API provides a wealth of data for developers and researchers interested in exploring the content and history of one of the world's most respected news organizations.

How do I transfer data from New York Times to Google PubSub?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up New York Times as a source connector (using Auth, or usually an API key)
2. Set up Google PubSub as a destination connector
3. Define which data you want to transfer and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

What are top ETL tools to extract data from

The most prominent ETL tools to transfer data from New York Times to Google PubSub include:
- Airbyte
- Fivetran
- StitchData
- Matillion
- Talend Data Integration
These tools help in extracting data from New York Times and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Google PubSub and other databases, data warehouses and data lakes, enhancing data management capabilities.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

New York Times to Google PubSub in minutes.

ETL your New York Times data into Google PubSub, in minutes, for free, with our open-source data integration connectors. In the format you need with post-load transformation.

We don't support the
Google PubSub
connector yet. Scroll down to upvote and prioritize it, or check our Connector Development Kit to build it within 2 hours.
We don't support the
New York Times
connector yet. Scroll down to upvote and prioritize it, or check our Connector Development Kit to build it within 2 hours.
We don't support the
New York Times
and
Google PubSub
connectors yet. Scroll down to upvote and prioritize them, or check our Connector Development Kit to build it within 2 hours.

Select the New York Times data that you want to replicate.

The New York Times source connector can be used to sync the following tables:

Archive API
Includes Internet Archive APIs.
Article search API
Includes Developer Network .
Books API
Books API
Community API
Includes Microservice API Patterns.
Most popular API
Includes Skyscanner, REST Countries, URL Shortener Service.
Movie reviews API
Includes Movie Database, Utelly API, IMDb API, GoWATCH API. RSS feeds Apology Line, Bible in Year, Crime Junkie, Experiment.

About New York Times

The Times Developer Network is our API clearinghouse and community. You need to read the API documentation and browse the application gallery to get the latest news about the New York Times API. If you do not agree to any of the terms below or the NYT Terms of Service, NYT does not grant you a license to use the NYT API. In the event of any inconsistency between these Terms of Use and the Terms of Service, these Terms of Use control.

Start analyzing your New York Times data in minutes with the right data transformation

airbyte data transformation screenshot

Full control over the data

You select the data you want to replicate, and this for each destination you want to replicate your

New York Times

data to.

Normalized schemas

You can opt for getting the raw data, or to explode all nested API objects in separate tables.

Custom transformation via dbt

You can add any dbt transformation model you want and even sequence them in the order you need, so you get the data in the exact format you need at your cloud data warehouse, lake or data base.

Airbyte is designed to address 100% of your Google PubSub needs

calendar icon

Scheduled updates

Automate replications with recurring incremental updates to

Google PubSub

.

play
Replicate Salesforce data to Snowflake with incremental

Manual full refresh

Easily re-sync all your data when

Google PubSub

has been desynchronized from the data source.

Change Data Capture for databases

Ensure your database are up to date with log-based incremental replication.

play
Check how log replication works for PostgreSQL

About Google PubSub

Google Pub/Sub is an asynchronous messaging service built to be both highly reliable and scalable. Based on a component of Google’s infrastructure, Pub/Sub offers the capabililty of sending more than 500 million messages (over 1 TB of data) per second.

Why Choose Airbyte for your New York Times and Google PubSub data integration

Airbyte is the new open-source ETL platform, and enables you to replicate your

New York Times

data in the destination of your choice, in minutes.

Maintenance-free

Heading

connector

Just authenticate your New York Times account and destination, and your new New York Times data integration will adapt to schema / API changes.

Extensible as open-sourced

With Airbyte, you can easily adapt the open-source New York Times ETL connector to your exact needs. All connectors are open-sourced.

No more security compliance issues​

Use Airbyte’s open-source edition to test your data pipeline without going through 3rd-party services. This will make your security team happy.

Normalized schemas​

Engineers can opt for raw data, analysts for normalized schemas. Airbyte offers several options that you can leverage with dbt.

Orchestration & scheduling​

Airbyte integrates with your existing stack. It can run with Airflow & Kubernetes and more are coming.

Monitoring & alerts on your terms​

Delays happen. We log everything and let you know when issues arise. Use our webhook to get notifications the way you want.

New York Times to Google Pubsub in minutes

ETL your New York Times data into Google PubSub, in minutes, for free, with our open-source data integration connectors. In the format you need with post-load transformation.

We don't support the
New York Times
connector yet. Scroll down to upvote and prioritize it, or check our Connector Development Kit to build it within 2 hours.
We don't support the
Google PubSub
connector yet. Scroll down to upvote and prioritize it, or check our Connector Development Kit to build it within 2 hours.
We don't support the
New York Times
and
Google PubSub
connectors yet. Scroll down to upvote and prioritize them, or check our Connector Development Kit to build it within 2 hours.

Airbyte is designed to address 100% of your New York Times database needs.

Full control over the data

The 

New York Times

 source does not alter the schema present in your database. Depending on the destination connected to this source, however, the schema may be altered.

calendar icon

Scheduled updates

Automate replications with recurring incremental updates.

Log-based incremental replication

Ensure your database are up to date with log-based incremental replication.

play
Check how log replication works for PostgreSQL

About New York Times

The Times Developer Network is our API clearinghouse and community. You need to read the API documentation and browse the application gallery to get the latest news about the New York Times API. If you do not agree to any of the terms below or the NYT Terms of Service, NYT does not grant you a license to use the NYT API. In the event of any inconsistency between these Terms of Use and the Terms of Service, these Terms of Use control.

Start analyzing your New York Times data in minutes with the right data transformation

airbyte data transformation screenshot

Full control over the data

You select the data you want to replicate, and this for each destination you want to replicate your New York Times data to.

Normalized schemas

You can opt for getting the raw data, or to explode all nested API objects in separate tables.

Custom transformation via dbt

You can add any dbt transformation model you want and even sequence them in the order you need, so you get the data in the exact format you need at your cloud data warehouse, lake or data base.

Airbyte is designed to address 100% of your Google PubSub needs

calendar icon

Scheduled updates

Automate replications with recurring incremental updates to Google PubSub.

play
Replicate Salesforce data to Snowflake with incremental

Manual full refresh

Easily re-sync all your data when Google PubSub has been desynchronized from the data source.

Change Data Capture for databases

Ensure your database are up to date with log-based incremental replication.

play
Check how log replication works for PostgreSQL

About Google PubSub

Google Pub/Sub is an asynchronous messaging service built to be both highly reliable and scalable. Based on a component of Google’s infrastructure, Pub/Sub offers the capabililty of sending more than 500 million messages (over 1 TB of data) per second.

Why choose Airbyte for your New York Times and Google PubSub data integration.

Airbyte is the new open-source ETL platform, and enables you to replicate your New York Times data in the destination of your choice, in minutes.

Maintenance-free

Heading

connector

Just authenticate your

New York Times

account and destination, and your new

New York Times

data integration will adapt to schema / API changes.

Extensible as open-sourced

With Airbyte, you can easily adapt the open-source

New York Times

ETL connector to your exact needs. All connectors are open-sourced.

No more security compliance issues​

Use Airbyte’s open-source edition to test your data pipeline without going through 3rd-party services. This will make your security team happy.

Normalized schemas​

Engineers can opt for raw data, analysts for normalized schemas. Airbyte offers several options that you can leverage with dbt.

Orchestration & scheduling​

Airbyte integrates with your existing stack. It can run with Airflow & Kubernetes and more are coming.

Monitoring & alerts on your terms​

Delays happen. We log everything and let you know when issues arise. Use our webhook to get notifications the way you want.