Fivetran + dbt Labs released dbt v2 and dbt State, delivering more speed and cost optimization, and introduced Fivetran Context Layer, new dbt Wizard experiences, dbt Charts, and an open lakehouse vision for greater flexibility across storage and compute.
dbt v2 is a Rust rewrite of the dbt engine built for the scale that teams run at today and for how agents write SQL. It parses a 10,000-model project faster and gives teams and agents real-time feedback, surfacing errors, column checks, and lineage before anything runs. With this release dbt is one engine with two versions: dbt Core v1, the python implementation, is dbt v1. Fusion, the Rust implementation, has become dbt v2. Both versions remain Apache 2.0-licensed and security-supported.
dbt State determines what has changed by checking warehouse metadata and model SQL, then builds, skips, clones or defers each run accordingly. This simplifies orchestration and allows engineers to iterate without complex development rituals, while reducing unnecessary warehouse compute.
Fivetran + dbt Labs’ vision for Open Data Infrastructure centers on a customer-owned data layer built on open formats, avoiding vendor lock-in for storage and compute so organizations can store data once and access it through different engines for different use cases.
