HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of ggdist and Windmill — release velocity, themes, recent moves, and the top alternatives to consider.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
Windmill gave away the warehouse connectors and now runs dbt natively — the trial is the strategy.
Two lines are moving at once. The platform line made dbt projects a first-class runtime, unified the deployment target on workspace lineage, opened Compare & Deploy to arbitrary target workspaces, and moved BigQuery and Snowflake out from behind the Enterprise license. The AI line took sessions to beta on by default and has been adding controls around them since — file attachments, visible web-search sources, artifact version history, and now a read-only plan mode that refuses anything that writes or deploys until you approve a plan.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.
Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.
Two lines are moving at once. The platform line made dbt projects a first-class runtime, unified the deployment target on workspace lineage, opened Compare & Deploy to arbitrary target workspaces, and moved BigQuery and Snowflake out from behind the Enterprise license. The AI line took sessions to beta on by default and has been adding controls around them since — file attachments, visible web-search sources, artifact version history, and now a read-only plan mode that refuses anything that writes or deploys until you approve a plan.
Windmill is positioning as the place a data team's existing work already runs rather than a system to be ported to: an unmodified dbt project drops in, its models become addressable assets with ref() lineage, and the warehouse languages needed to reach them are no longer paywalled. In parallel, the AI session work is maturing from capability to governance — the recent additions are all about reviewability and constraint, not raw autonomy. The deployment changes point the same way, collapsing configurable targets into a single derived answer.
Expect the plan-and-approve posture to spread beyond session chats into the durable AI surfaces, and more warehouse-adjacent runtimes to follow dbt into the first-class treatment; Oracle and MS SQL remain the obvious Enterprise holdouts to watch.
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either ggdist or Windmill.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all ggdist alternatives → · See all Windmill alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Windmill is currently shipping more aggressively (velocity 8.8 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Windmill is currently shipping more aggressively (velocity 8.8 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top ggdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggdist alternatives" section above for the current picks, or visit /alternatives/ggdist for the full list with editorial commentary on each.
Top Windmill alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Windmill alternatives" section above for the current picks, or visit /alternatives/windmill for the full list with editorial commentary on each.