Two staging models, one sync
Snowflake loads through its internal stage, MotherDuck through your S3 bucket. You configure each once and Polytomic does the rest.
Move tables between Snowflake and MotherDuck with Polytomic. The two warehouses stage loads differently, Snowflake through its own internal stage and MotherDuck through Parquet files in your S3 bucket, and Polytomic handles both sides so ETL and reverse ETL run on a schedule rather than through custom pipelines.
Snowflake loads through its internal stage, MotherDuck through your S3 bucket. You configure each once and Polytomic does the rest.
Snowflake VARIANT and ARRAY columns map onto DuckDB STRUCT and LIST rather than being flattened into text on the way across.
Tables with a primary key are reconciled on every run, so a Snowflake table synced hourly does not accumulate duplicate rows in MotherDuck.

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Follow these simple steps to connect MotherDuck with Snowflake in minutes
Connect MotherDuck
Connect Snowflake
Create sync
Enable sync
Connect MotherDuck to Polytomic with an access token and your database name.
Connect Snowflake to Polytomic with account details, a role, a warehouse, and credentials.
Sync data in either direction between MotherDuck and Snowflake. Choose the source data and destination objects for the direction you need.
Map the fields, choose the sync schedule and behavior, then save and enable the sync.
Get answers to common questions about the integration process
Sync data in either direction between MotherDuck and Snowflake.
Use both integrations' source and destination capabilities in one managed sync workflow.
Enterprise encryption and security protocols ensure your data remains protected.
Get up and running in minutes with our step-by-step integration guide.