Can you use Fivetran with Snowflake?

Quick Answer: Yes. Snowflake is one of Fivetran's primary destinations. Fivetran automatically creates schemas, tables, and columns in Snowflake, handles incremental loading, and manages schema changes without manual intervention. As of April 2026, over half of Fivetran customers use Snowflake as their data warehouse.

Using Fivetran with Snowflake

Fivetran provides first-class integration with Snowflake as a data warehouse destination. As of April 2026, Snowflake is one of the most commonly used destinations on the Fivetran platform, and the integration supports all Fivetran connector types.

Automatic Schema Management

Fivetran automatically manages the target schema in Snowflake:

  • Schema creation — Fivetran creates a dedicated schema for each connected source
  • Table creation — Tables are created automatically based on the source structure
  • Column addition — New columns discovered in the source are added to Snowflake tables
  • Data type mapping — Source data types are mapped to appropriate Snowflake data types
  • Schema change handling — Column renames, type changes, and deletions are handled with configurable policies

Incremental Loading

Fivetran uses incremental sync strategies to minimize data transfer and Snowflake compute costs:

  • Change Data Capture (CDC) for supported database sources (PostgreSQL, MySQL, SQL Server)
  • API-based incremental loading using cursor or timestamp fields
  • Merge operations for upserts, preserving historical data

Setup Process

  1. In Fivetran, create a new destination and select Snowflake
  2. Enter the Snowflake account identifier, database name, and warehouse name
  3. Provide a Fivetran service user with appropriate Snowflake roles and permissions
  4. Fivetran tests the connection and confirms write access
  5. Add connectors (sources) and select the Snowflake destination
  6. Fivetran performs an initial full sync, then switches to incremental

Performance Optimization

  • Fivetran uses Snowflake's COPY INTO command for bulk loading
  • Staging files are stored in a Fivetran-managed cloud storage bucket
  • Teams can configure the Snowflake warehouse size to control sync speed and cost
  • Sync frequency is configurable from 1 minute to 24 hours

Cost Considerations

Fivetran pricing is based on Monthly Active Rows (MAR), independent of Snowflake costs. Snowflake charges separately for compute (warehouse credits) and storage. Teams should right-size the Snowflake warehouse dedicated to Fivetran loading to control costs.

Fivetran Transformations in Snowflake

Fivetran offers built-in SQL transformations that run directly in Snowflake after data loading completes. This enables teams to create staging tables, join sources, and build analytics-ready datasets without a separate transformation tool like dbt.

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Written & reviewed by Rafal Fila · Last updated:

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