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sidebar_label sidebar_position slug keywords description
Deepnote
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/en/integrations/deepnote
clickhouse
Deepnote
connect
integrate
notebook
Efficiently query very large datasets, analyzing and modeling in the comfort of known notebook environment.

import ConnectionDetails from '@site/docs/en/_snippets/_gather_your_details_http.mdx';

Connect ClickHouse to Deepnote

Deepnote is a collaborative data notebook built for teams to discover and share insights. In addition to being Jupyter-compatible, it works in the cloud and provides you with one central place to collaborate and work on data science projects efficiently.

This guide assumes you already have a Deepnote account and that you have a running ClickHouse instance.

Interactive example

If you would like to explore an interactive example of querying ClickHouse from Deepnote data notebooks, click the button below to launch a template project connected to the ClickHouse playground.

Connect to ClickHouse

  1. Within Deepnote, select the "Integrations" overview and click on the ClickHouse tile.

<img src={require('./images/deepnote_01.png').default} class="image" alt="ClickHouse integration tile" style={{width: '100%'}}/>

  1. Provide the connection details for your ClickHouse instance:

<img src={require('./images/deepnote_02.png').default} class="image" alt="ClickHouse details dialog" style={{width: '100%'}}/>

NOTE: If your connection to ClickHouse is protected with an IP Access List, you might need to allow Deepnote's IP addresses. Read more about it in Deepnote's docs. 3. Congratulations! You have now integrated ClickHouse into Deepnote.

Using ClickHouse integration.

  1. Start by connecting to the ClickHouse integration on the right of your notebook.

    <img src={require('./images/deepnote_03.png').default} class="image" alt="ClickHouse details dialog" style={{width: '100%'}}/>

  2. Now create a new ClickHouse query block and query your database. The query results will be saved as a DataFrame and stored in the variable specified in the SQL block.

  3. You can also convert any existing SQL block to a ClickHouse block.