How to load data from Confluence to Clickhouse

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

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

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How to Sync to Manually

Step 1: Export Data from Confluence

Begin by exporting the data you need from Confluence. If your data is stored within Confluence pages, use the built-in export functionality. Navigate to the page or space you want to export, and use the "Export" option under the "..." menu. Choose a format that ClickHouse can process, such as CSV or XML. Download the exported file to your local system.

If your exported data is not in CSV format, you need to convert it. Use a script or a tool like a spreadsheet editor to transform the data into CSV format. Ensure that your CSV file has properly defined headers and a consistent structure, as this will facilitate the import process into ClickHouse.

Before importing data, set up a table in ClickHouse to accommodate the incoming data. Use the ClickHouse client or an SQL interface to define a table schema that matches the structure of your CSV data. This ensures that the data aligns properly with the table columns when you load it.

Move your CSV file to the server where ClickHouse is hosted. You can use secure methods such as SCP (Secure Copy Protocol) or SFTP (Secure File Transfer Protocol) to upload the CSV file. Ensure the file is placed in a directory accessible by the ClickHouse server.

Use the ClickHouse command-line client to load your CSV data into the prepared table. Execute a command like:
```
clickhouse-client --query="INSERT INTO your_table FORMAT CSV" < /path/to/your/file.csv
```
This command reads the CSV file and inserts the data directly into the specified ClickHouse table. Ensure that the CSV delimiter matches the default or configured delimiter in ClickHouse.

After loading the data, it is crucial to verify its integrity. Run a set of queries to check that the data has been correctly imported and matches the original dataset from Confluence. Look for discrepancies in record counts, data types, and content accuracy.

Finally, optimize the newly imported data for performance. Create necessary indexes, partition tables if needed, and run any optimization commands available in ClickHouse. This step ensures that your data warehouse operates efficiently and can handle queries swiftly.