How Fivetran, dbt, and Databricks Lakeflow work together

Fivetran, dbt, and Databricks Lakeflow are presented as complementary components of a modern data platform rather than direct competitors: Fivetran manages ingestion from more than 770 SaaS applications and databases, dbt creates tested, documented SQL-based business models, and Lakeflow handles custom batch and streaming pipelines plus orchestration. In an account-health use case, Fivetran loads Salesforce, billing, support, and application data into Databricks, while Lakeflow processes Kafka product events such as logins and feature usage; dbt then standardizes commercial and support data, and Lakeflow combines these models with usage signals into a continuously updated account-health table. The approach is positioned for organizations with diverse enterprise sources, analytics teams reliant on SQL modeling, and engineering needs involving real-time data, AI, machine learning, or unstructured processing, allowing teams to preserve existing dbt assets while reducing connector maintenance and building custom data products.

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