Sparkflows on Snowflake
Enable Data analysts &
Data scientists to seamlessly perform advanced analytics on the data on Snowflake
Organizations are making Snowflake the center of their data warehousing strategy. With Sparkflows self-serve advanced analytics capabilities seamlessly enable your data science capabilities. With 340+ processors running in a distributed manner, covering data preparation, data exploration, and ML model building, Sparkflows enables comprehensive advanced analytics directly within your Snowflake data warehouse.
Seamlessly read from and write to Snowflake at Scale.
Sparkflows Apache Spark Snowflake connector makes it fast and scalable to read from and write to Snowflake.
Push down Analytics to Snowflake
The workflows in Sparkflows push down analytics to Snowflake. A number of operations including read, filter, joins etc are supported as push down via the snowflake connector.
Seamlessly create secured connections to snowflake
Sparkflows enables seamless creation of snowflake connections. The credentials are stored encrypted in the credential store.
Connections can be at global, project or group level. It makes it easy and secure for teams to access snowflake.
Read and writes from Snowflake
