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Comparison · Infra & APIs

profileCI vs Windmill

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

profileCI vs Windmill: at a glance

FeatureprofileCIWindmill
SectorInfra & APIsInfra & APIs
Velocity score0.08.8
Sparks · 30d02
Top themesprofile-likelihood, confidence-intervals, statistics, numerical-robustnessworkflow orchestration, dbt, open core, ai sessions
Last editorial update39m ago1d ago
WebsiteVisit →Visit →

What is profileCI?

Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.

profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.

Read the full profileCI trajectory →

What is Windmill?

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

In a single fortnight Windmill moved BigQuery and Snowflake out of the Enterprise license and made dbt projects a first-class runtime executing on the customer's own workers. Around that, deployment got simpler — one target derived from workspace lineage, compare-and-deploy into any workspace — and the AI session surface keeps thickening: markdown artifacts, then version history over those artifacts with the assistant able to read past versions.

Read the full Windmill trajectory →

profileCI vs Windmill: editorial side-by-side

P
profileCI
INFRA · APIS
0.0

Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.

◆ Current state

profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.

◆ Where it's heading

Work is concentrated on numerical reliability rather than scope: 1.1.1 replaced quadratic with monotonic cubic spline interpolation because the quadratic form could fail, and corrected parameter values stored near the confidence limits. The feed publishes these out of order, with the v1.0.0 entry stamped six months after v1.1.0 and carrying the package's full description rather than a changelog, so release order should be read from the version numbers rather than the dates. The same maintainer's revdbayes has been in pure maintenance across this period, which places profileCI as the more active project.

◆ Prediction

Expect further robustness work at the profiling limits and more logLikFn methods for common model classes, following the nls method added in 1.1.0.

W
Windmill
INFRA · APIS
8.8

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

◆ Current state

In a single fortnight Windmill moved BigQuery and Snowflake out of the Enterprise license and made dbt projects a first-class runtime executing on the customer's own workers. Around that, deployment got simpler — one target derived from workspace lineage, compare-and-deploy into any workspace — and the AI session surface keeps thickening: markdown artifacts, then version history over those artifacts with the assistant able to read past versions.

◆ Where it's heading

The community edition is being loaded up with exactly what a data team needs to run a real trial: warehouse connectors, an unmodified dbt project, storage quota instead of an upload cap. Enterprise is being repositioned around scale and governance rather than feature access. The AI sessions track is developing on its own clock, moving from chat toward durable, versioned work products that survive a session.

◆ Prediction

Expect AI session artifacts to gain server-side persistence and sharing, since they are still stored in the browser and tied to the session. On the data side, the dbt runtime is likely to grow scheduling and lineage integration with the pipelines alpha rather than staying a standalone script language.

Alternatives to profileCI 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 profileCI or Windmill.

See all profileCI alternatives → · See all Windmill alternatives →

Recent activity from profileCI and Windmill

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

  1. 5d agoWindmillNested filter groups and dotted paths in trigger filters
  2. 6d agoWindmillVersion history for AI session artifacts
  3. 15d agoWindmillRun dbt projects as a first-class Windmill runtime
  4. 17d agoWindmillCompare & Deploy into any workspace
  5. 17d agoWindmillOne deployment target, derived from the workspace lineage
  6. 22d agoWindmillBigQuery and Snowflake available in the community edition
  7. 6mo agoprofileCICubic spline interpolation replaces a quadratic that could fail
  8. 7mo agoprofileCICRAN 1.0.0 release of profile-likelihood interval computation
  9. 1y agoprofileCIInfinite limits and bounded profiling ranges handled

Frequently asked questions

What is the difference between profileCI 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 2 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 profileCI 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 2 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 profileCI?

Top profileCI alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "profileCI alternatives" section above for the current picks, or visit /alternatives/profileci 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.