daedalus
An epidemic-economic model teaching its interventions to react to the outbreak itself.
Comparison · Infra & APIs
adjustedCurves vs Windmill
A side-by-side editorial comparison of adjustedCurves and Windmill — release velocity, themes, recent moves, and the top alternatives to consider.
adjustedCurves vs Windmill: at a glance
What is adjustedCurves?
A survival curve package spending release after release correcting its own estimates
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
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.
adjustedCurves vs Windmill: editorial side-by-side
adjustedCurves
0.0INFRA · APIS
A survival curve package spending release after release correcting its own estimates
◆ Current state
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
◆ Where it's heading
Multiple imputation is the recurring fault line. The standard error pooling formula was implemented incorrectly until 0.11.2, then fixed again in 0.11.3 for the bootstrapping-plus-imputation combination, and 0.11.4 added the pooled risk table values that had previously been omitted entirely. A separate thread quietly removed capability: tmle and ostmle methods went in 0.10.0, and tmle support was pulled again in 0.11.1 after the concrete package left CRAN. Feature work does happen - risk tables, contrast arguments, the extend_to_last control on IPTW curves - but it is outweighed by correction.
◆ Prediction
Expect continued estimator-level corrections rather than new methods, and a possible return of tmle support if its upstream dependency returns to CRAN, since the removal was described as temporary.
Windmill
8.8INFRA · APIS
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 adjustedCurves 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 adjustedCurves or Windmill.
bkmrhat
A parallel-chain helper for bkmr that has settled into pure upkeep.
driveR
A cancer driver prioritization package that ships rarely and mostly to stay installable
metR
A meteorology ggplot2 extension where the netCDF reader became the main event
IsoriX
An isotope geolocation package still recovering from the r-spatial retirement
fdacluster
Functional data clustering grew from one algorithm into a comparable suite
See all adjustedCurves alternatives → · See all Windmill alternatives →
Recent activity from adjustedCurves and Windmill
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4d agoWindmillPlan mode for AI sessions
- 7d agoWindmillNested filter groups and dotted paths in trigger filters
- 8d agoWindmillVersion history for AI session artifacts
- 17d agoWindmillRun dbt projects as a first-class Windmill runtime ⚡
- 19d agoWindmillOne deployment target, derived from the workspace lineage
- 19d agoWindmillCompare & Deploy into any workspace
- 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
- 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
- 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
- 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
- 3y agoadjustedCurvestmle and ostmle methods dropped
- 3y agoadjustedCurvesDependency compatibility and installation documentation
Frequently asked questions
What is the difference between adjustedCurves 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 adjustedCurves 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 adjustedCurves?
Top adjustedCurves alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "adjustedCurves alternatives" section above for the current picks, or visit /alternatives/adjustedcurves 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.