Snowflake is a cloud-based SQL data warehouse that focuses on great performance, zero-tuning, diversity of data sources, and security. This article explains how to read data from and write data to Snowflake using the Azure Databricks Snowflake connector.

Azure Databricks and Snowflake have partnered to bring a first-class connector experience for customers of both Azure Databricks and Snowflake, saving you from having to import and load libraries into your clusters, and therefore preventing version conflicts and misconfiguration.



The Azure Databricks Snowflake connector is available in Databricks Runtime 4.2 and above.

Use the Azure Databricks Snowflake connector

The following notebooks provide simple examples of how to write data to and read data from Snowflake. See Using the Connector in the Snowflake documentation for more details.


Avoid exposing your Snowflake username and password in notebooks by using the Secrets feature, which is demonstrated in the sample notebooks below.

Snowflake Scala notebook

Get notebook

Snowflake Python notebook

Get notebook

Snowflake R notebook

Get notebook

Train a machine learning model using Snowflake

Demo Snowflake notebook

Get notebook

Frequently asked questions (FAQ)

Why don’t my Spark DataFrame columns appear in the same order in Snowflake?

The Spark - Snowflake connector doesn’t respect the order of the columns in the table being written to; you must explicitly specify the mapping between DataFrame and Snowflake columns. To specify this mapping, use the columnmap parameter.

Why is INTEGER data written to Snowflake always read back as DECIMAL?

Snowflake represents all INTEGER types as NUMBER, which can cause a change in data type when you write data to and read data from Snowflake. For example, INTEGER data can be converted to DECIMAL when writing to Snowflake, because INTEGER and DECIMAL are semantically equivalent in Snowflake (see Snowflake Numeric Data Types).

Why are the fields in my Snowflake table schema always uppercase?

Snowflake uses uppercase fields by default, which means that the table schema is converted to uppercase.