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collapse vs epikit

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

Shared themes:r-package

collapse vs epikit: at a glance

Featurecollapseepikit
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsepidemiology, field-data, date-handling, r-package
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is epikit?

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

Read the full epikit trajectory →

collapse vs epikit: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

E
epikit
ANALYTICS
0.0

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

◆ Current state

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

◆ Where it's heading

The package is being scoped down rather than built out. The 0.1.3 restructuring and the 0.2.0 handover of proportions to epitabulate are the same move made twice: push functionality into the package where it belongs and keep epikit to the toolkit that field epidemiologists reach for directly. The rest of the history is dependency compatibility work against dplyr and tibble.

◆ Prediction

With proportions gone and dependencies trimmed, the remaining functions cluster tightly around dates and age bands, so further refinement of the date-reconstruction helpers is more likely than new capability areas.

Alternatives to collapse and epikit

Other Analytics 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 collapse or epikit.

See all collapse alternatives → · See all epikit alternatives →

Recent activity from collapse and epikit

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

  1. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  2. 7mo agocollapseNegative zero now hashes equal to zero across the package
  3. 8mo agocollapsecollap() no longer double-aggregates external weights
  4. 9mo agoepikitProportion functions moved to epitabulate; date helpers warn correctly
  5. 9mo agocollapseCustom unlist() preserves attributes
  6. 0y agocollapseAssorted bug fixes
  7. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  8. 3y agoepikitFunctions rearranged across sibling packages
  9. 5y agoepikitRaise dplyr and tibble minimums; move CI to GitHub Actions
  10. 5y agoepikitCompatibility release for dplyr 1.0.0
  11. 6y agoepikitFirst CRAN release

Frequently asked questions

What is the difference between collapse and epikit?

Both compete on the same themes — r-package — within Analytics. collapse and epikit are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is collapse better than epikit?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collapse and epikit are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to collapse?

Top collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.

What are the best alternatives to epikit?

Top epikit alternatives in Analytics are ranked by recent ship velocity. Browse the "epikit alternatives" section above for the current picks, or visit /alternatives/epikit-r for the full list with editorial commentary on each.