Databricks

Databricks ranks 80th overall in the platforms category with a composite score of 59 out of 100. The organization describes itself as Helping data teams solve the world’s toughest problems using data and AI, which frames how developers first encounter the brand on GitHub, in package registries and in search results.

Its shipping velocity and developer reach come across as strong, and are what most developers will notice first when they land on the organization. By contrast, its developer experience and community engagement 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.

Databricks maintains 256 public repositories on GitHub, built primarily in Java, Python and Scala, which together have collected 37,949 stars and drawn contributions from 3 developers outside the core team, 38 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 Databricks 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.