Snowflake

Snowflake is a cloud-based data warehousing platform for storing and analyzing large volumes of data. It provides a scalable architecture for real-time analytics, making it ideal for business intelligence applications.

What you can do with this integration

The integration for Snowflake lets you:

• Read users from a Snowflake database and unify them as user profiles inside Krenalis.
• Write unified users back into Snowflake and keep the target table synchronized over time.

You can use it both to collect user data and to activate user profiles.

• 

  Ingest users

  Read and sync user data from Snowflake into your workspace.

• 

  Activate users

  Write unified profiles to Snowflake and keep the data updated.

Do incremental imports in query

If the incremental import is enabled, you must use the updated_at placeholder in the query, as shown in the following example:

SELECT first_name, last_name, phone_number
FROM customers
WHERE updated_at >= ${updated_at}
ORDER BY updated_at

The column used in the WHERE statement must be the same column selected as the update time column in the pipeline, and the query must return the rows ordered by this column in ascending order. For example, if the update time column is a datetime column and the update time is 2025-01-30 16:12:25.837, the executed query would be:

SELECT first_name, last_name, phone_number
FROM customers
WHERE updated_at >= '2025-01-30 16:12:25.837'
ORDER BY updated_at

If incremental import is not selected, ${updated_at} will be NULL. To make the query work whether or not incremental import is enabled, you can write it as follows:

SELECT first_name, last_name, phone_number
FROM customers
WHERE updated_at >= ${updated_at} OR ${updated_at} IS NULL 
ORDER BY updated_at