Sync from New York Times to Apache Iceberg

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

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Start syncing data from New York Times to Apache Iceberg in three easy steps

Setup a New York Times connector in Airbyte

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

Set up Apache Iceberg as the destination connector

Connect to Apache Iceberg or one of 50+ Airbyte data destinations through simple account authentication

Sync your Data

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

Get started for free

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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 Apache Iceberg

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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 Apache Iceberg?

For huge analytical tables, Apache Iceberg is a high-performance format. Using Apache Iceberg, engines such as Spark, Trino, Flink, Presto, Hive and Impala can safely work with the same tables, at the same time, providing the reliability and simplicity of SQL tables to big data. With Apache Iceberg, you can merge new data, update existing rows, and delete specific rows. Data files can be eagerly rewritten or deleted deltas can be used to make updates faster.

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 Apache Iceberg?

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 Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg in minutes.

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

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We don't support the

Apache Iceberg

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

Apache Iceberg

connectors yet. Scroll down to upvote and prioritize them, or check our Connector Development Kit to build it within 2 hours.

Others

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

Community API

Includes Microservice API Patterns.

About New York Times

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

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 Apache Iceberg needs

Scheduled updates

Automate replications with recurring incremental updates to

Apache Iceberg

Replicate Salesforce data to Snowflake with incremental

Manual full refresh

Easily re-sync all your data when

Apache Iceberg

has been desynchronized from the data source.

Change Data Capture for databases

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

Check how log replication works for PostgreSQL

Check the docs

View this Apache Iceberg connector to upvote it

About Apache Iceberg

Why Choose Airbyte for your New York Times and Apache Iceberg 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.

Check out our features

New York Times to Apache Iceberg in minutes

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

Get started for free

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

Apache Iceberg

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

Apache Iceberg

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.

Scheduled updates

Automate replications with recurring incremental updates.