How dbt Labs and Fivetran are moving dbt workloads onto the data lake, model by model
Blog post from dbt
dbt Labs and Fivetran argue that open data lakes based on Apache Iceberg and open catalog interfaces can reduce the cost, vendor dependence, and disruption associated with traditional warehouse-centric data stacks. Their approach allows organizations to migrate incrementally by moving individual tables from proprietary warehouse formats to Iceberg while retaining existing namespaces, dbt dependencies, and BI dashboards. Fivetran demonstrated a managed data lake setup and a “Move” capability that transferred a Snowflake-native table to Iceberg in minutes, with an estimated 15–20% reduction in Snowflake compute costs for that workload. The companies also presented Lake Compute, which enables teams to shift selected simple dbt transformations to less expensive lake-native compute without restructuring projects, while leaving downstream analytics-facing models in the warehouse. They framed the architecture as a standards-based foundation that can be assembled with open-source tools or operated through managed Fivetran services.
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