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With the ClickHouse integration, you can leverage the performance and scalability that comes with ClickHouse's open-source column-oriented DBMS right from within Deepnote. ClickHouse allows users to handle thousands of sub-second queries per second on petabyte-scale datasets. If you need to run fast queries against (very) large datasets, ClickHouse is for you.


Deepnote's ClickHouse integration allows data teams to efficiently query very large datasets, extract relevant data, and start analyzing and modeling in the comfort of their known notebook environment.

How to connect

To create a ClickHouse integration in Deepnote, open up the integrations overview and click on the ClickHouse tile.

To create the integration, you'll need a few things:

  • Hostname: The hostname of the server you are trying to connect to. Check out this section of ClickHouse's docs for more details.
  • Port: The port on the server of interest you are trying to connect to. Luckily, ClickHouse's docs offer concrete steps for this one as well.
  • Username: Your username. More in ClickHouse's docs here.
  • Password: The password for the specified username. More details here.
  • Database: The name of the database you would like to connect to.

How to use

Once created, you'll be able to connect the ClickHouse integration to any project within your workspace through the right-hand sidebar. The ClickHouse integration comes with custom ClickHouse SQL blocks that help streamline your analytics efforts. You can also convert any existing SQL block to a ClickHouse block.

As with all SQL blocks, the query results will be saved as a dataframe and stored in the variable specified in the SQL block.

Next steps

Jump right into Deepnote & learn more about SQL blocks in this A/B testing template. You can also save yourself some setup work by hitting the Duplicate button in the top-right corner to start exploring on your own!

Secure connections

Deepnote supports securing connections to ClickHouse via optional SSH tunnels.