> For the complete documentation index, see [llms.txt](https://docs.predicthq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicthq.com/integrations/third-party-integrations/integrate-with-databricks.md).

# Integrate with Databricks

The best methods for getting PredictHQ data into Databricks is via S3 or Snowflake.

Databricks provides native integrations with AWS S3 as well as Snowflake (among other sources) and there are a number of options for pulling in or accessing data stored in these platforms.

We can provide full or incremental dumps of data via AWS Data Exchange (ADX) which you can configure to automatically store in S3. We can also provide regularly updated shared tables in Snowflake.

Get in touch with us to talk about receiving data via ADX or Snowflake.

Some resources on the Databricks side that should be referred to when looking at pulling data from S3 or Snowflake into Databricks:

{% embed url="<https://docs.databricks.com/en/storage/amazon-s3.html>" %}

{% embed url="<https://docs.databricks.com/en/external-data/amazon-s3-select.html>" %}

{% embed url="<https://docs.databricks.com/en/external-data/snowflake.html>" %}


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