How to load data from News API to Clickhouse

Learn how to use Airbyte to synchronize your News API data into Clickhouse within minutes.

Try Airbyte Cloud Manual method (the hard way)

Building your pipeline or Using Airbyte

Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:

Reliable and accurate
Extensible and scalable for all your needs
Deployed and governed your way

All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a News API connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Clickhouse for your extracted News API data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the News API to Clickhouse in Airbyte

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

Try Airbyte Cloud Manual method (the hard way)

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

Simple & Easy to use Interface

Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.

Guided Tour: Assisting you in building connections

Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.

Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes

Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.

Try Airbyte Cloud Manual method (the hard way)

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Learn more

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

Learn more

How to Sync to Manually

Step 1: Set Up ClickHouse Environment

Begin by installing ClickHouse on your server or local machine. You can do this by downloading the appropriate package from the ClickHouse official website and following the installation instructions for your operating system. Ensure that ClickHouse is running and accessible on your network.

Step 2: Create ClickHouse Table for News Data

Define a table schema in ClickHouse that will store the data you retrieve from the News API. Use SQL to create a table with appropriate columns, such as `title`, `description`, `publishedAt`, `author`, and `source`. For example:
```sql
CREATE TABLE news_data (
title String,
description String,
publishedAt DateTime,
author String,
source String
) ENGINE = MergeTree()
ORDER BY publishedAt;
```

Step 3: Access News API

Obtain an API key from the News API by registering on their website. Once you have your key, use it to make HTTP GET requests to the News API endpoint to fetch news articles. Typically, you would use a programming language like Python to make these requests, utilizing libraries such as `requests` to handle the HTTP communication.

Step 4: Extract and Transform Data

Write a script to extract the data from the JSON response received from the News API. Parse the JSON to obtain the relevant fields (title, description, published date, etc.) and transform them into a format suitable for insertion into ClickHouse. Ensure that data types are consistent with the ClickHouse table schema.

Step 5: Prepare Data for Insertion

Format the extracted data into an SQL `INSERT` query or a CSV file that ClickHouse can process. If using an SQL query, batch multiple records together to optimize performance. If using a CSV file, ensure the fields are separated correctly and match the schema defined in ClickHouse.

Step 6: Insert Data into ClickHouse

Execute the data insertion into ClickHouse. If using SQL `INSERT` queries, connect to ClickHouse using a command-line tool or a script and execute the queries. If using a CSV file, use ClickHouse's `clickhouse-client` utility to import the data:
```bash
clickhouse-client --query="INSERT INTO news_data FORMAT CSV" < data.csv
```
Ensure that the ClickHouse server is configured to accept connections from your client.

Step 7: Automate the Data Pipeline

Create a script or cron job to automate the data retrieval and insertion process. This script should periodically call the News API, process the data, and insert it into ClickHouse at regular intervals. This ensures that your ClickHouse database stays updated with the latest news articles without manual intervention.

By following these steps, you can efficiently move data from the News API to a ClickHouse warehouse without relying on third-party connectors or integrations.