How to load data from Notion to Clickhouse
Learn how to use Airbyte to synchronize your Notion data into Clickhouse within minutes.
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
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
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.
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
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend
Chase Zieman
“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.”
Rupak Patel
"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."
How to Sync to Manually
Step 1: Export Data from Notion
Begin by exporting your data from Notion. Navigate to the page or database you want to export. Click on the three dots in the top-right corner of the page and select "Export." Choose a format that suits your needs, such as CSV or Markdown, and download the file to your local machine.
Step 2: Prepare Data for Import
Once you've exported your data, review the file format. If it's in CSV, open it in a spreadsheet application like Excel or Google Sheets to ensure the data is correctly structured. Clean up any unnecessary columns or rows and save the file in CSV format.
Step 3: Set Up ClickHouse Environment
Ensure that ClickHouse is installed and running on your server or local machine. You can download the latest version from the ClickHouse official website and follow the installation instructions. Verify the installation by running a simple query using the ClickHouse client.
Step 4: Create a ClickHouse Table
Design a ClickHouse table schema that matches the structure of your Notion data. Use the ClickHouse SQL command to create the table. For example:
```sql
CREATE TABLE notion_data (
id String,
name String,
date Date,
value Float32
) ENGINE = MergeTree()
ORDER BY id;
```
Adjust the columns and data types as needed to match your CSV file.
Step 5: Transfer CSV File to ClickHouse Server
Transfer the CSV file to the machine where ClickHouse is running. You can use SCP (Secure Copy Protocol) or any other file transfer method that you are comfortable with. Ensure that the file is placed in an accessible directory on the server.
Step 6: Import Data into ClickHouse
Use the ClickHouse `clickhouse-client` to import the data from the CSV file into your ClickHouse table. Execute the following command:
```bash
clickhouse-client --query="INSERT INTO notion_data FORMAT CSV" < /path/to/your/notion_data.csv
```
Ensure the path to your CSV file is correct and matches the schema you created in the ClickHouse table.
Step 7: Verify Data Import
After importing the data, verify that it has been successfully transferred. Run a simple query to check the data:
```sql
SELECT * FROM notion_data LIMIT 10;
```
This will display the first 10 rows of your imported data, allowing you to confirm that the data is correctly loaded and accessible in ClickHouse. Adjust the query as needed to further verify data integrity.