dbt Labs

dbt Labs ranks 160th overall in the developer tools category with a composite score of 54 out of 100. The organization describes itself as dbt helps data teams work like software engineers-to ship trusted data, faster, which frames how developers first encounter the brand on GitHub, in package registries and in search results.

Its documentation and learning material and shipping velocity come across as strong, and are what most developers will notice first when they land on the organization. By contrast, its developer experience and developer reach look minimal today, which is the clearest area where a small amount of focused work would visibly move the needle. Taken together, the picture is of a company whose public developer surface is neither uniformly polished nor uniformly weak, and where different audiences (contributors, integrators, evaluators) will likely form very different first impressions depending on which door they walk through.

dbt Labs maintains 408 public repositories on GitHub, built primarily in Rust, Makefile and Python, which together have collected 27,075 stars and drawn contributions from 121 developers outside the core team, 57 of those repositories have seen commits in the last 90 days, a useful proxy for how much of the codebase is genuinely alive rather than archived.

For anyone evaluating dbt Labs as a technology choice, weighing a contribution, integrating the APIs, or comparing it against similar companies in the space, the sections below break down each of these signals in detail and link straight through to the underlying repositories, documentation and community threads that inform the score.