ClickHouse + dbt: Building a GitOps workflow at Twilio

At dbt Summit 2026, Twilio’s Voice & Video Insights team described how it replaced a decade-old pipeline built on Kafka, Spark Streaming, and Elasticsearch with a unified ClickHouse-based architecture managed through dbt and GitOps practices. The change reduced operational complexity by using ClickHouse materialized views for streaming transformations formerly handled by custom Spark applications, while dbt provided version-controlled SQL models, testing, lineage, and auditable deployment workflows. Twilio evolved from manually documented schema changes to GitHub-based schema-as-code and ultimately separated its dbt work into product-specific projects with shared logic, orchestrated by Argo Workflows. Engineers can test against real ClickHouse containers locally and in CI and deploy isolated preview databases per branch using production-data slices. The team also contributed materialized-view model update functionality to the open-source dbt-clickhouse adapter, while ClickHouse announced continued support for its dbt v1 adapter, a public beta for a near-feature-complete dbt v2 adapter, and private-beta ClickHouse support in the dbt platform.

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