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Comparison · Infra & APIs

ggdist vs Windmill

A side-by-side editorial comparison of ggdist and Windmill — release velocity, themes, recent moves, and the top alternatives to consider.

ggdist vs Windmill: at a glance

FeatureggdistWindmill
SectorInfra & APIsInfra & APIs
Velocity score0.08.8
Sparks · 30d01
Top themesdata-visualization, uncertainty, bayesian-statistics, ggplot2workflow orchestration, dbt, open core, ai sessions
Last editorial update47m ago16h ago
WebsiteVisit →Visit →

What is ggdist?

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.

Read the full ggdist trajectory →

What is Windmill?

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.

Read the full Windmill trajectory →

ggdist vs Windmill: editorial side-by-side

G
ggdist
INFRA · APIS
0.0

The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

W
Windmill
INFRA · APIS
8.8

Windmill gave away the warehouse connectors and now runs dbt natively — the trial is the strategy.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to ggdist and Windmill

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.

See all ggdist alternatives → · See all Windmill alternatives →

Recent activity from ggdist and Windmill

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4d agoWindmillPlan mode for AI sessions
  2. 7d agoWindmillNested filter groups and dotted paths in trigger filters
  3. 8d agoWindmillVersion history for AI session artifacts
  4. 17d agoWindmillRun dbt projects as a first-class Windmill runtime
  5. 19d agoWindmillOne deployment target, derived from the workspace lineage
  6. 19d agoWindmillCompare & Deploy into any workspace
  7. 1y agoggdistPer-geometry thickness subscales and settable defaults
  8. 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator
  9. 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
  10. 3y agoggdistBounded density becomes the default; existing charts change
  11. 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
  12. 4y agoggdistComputed variables shared across sub-geometries

Frequently asked questions

What is the difference between ggdist and Windmill?

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.

Is ggdist better than Windmill?

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.

What are the best alternatives to ggdist?

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.

What are the best alternatives to Windmill?

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.