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cheapr vs collapse

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

Shared themes:performancesimdr-package

cheapr vs collapse: at a glance

Featurecheaprcollapse
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesperformance, parallelism, simd, c-apidata-transformation, performance, simd, grouped-statistics
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is cheapr?

cheapr turned multi-threaded, and its next stop is a C++20 public API.

cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.

Read the full cheapr trajectory →

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 →

cheapr vs collapse: editorial side-by-side

C
cheapr
ANALYTICS
0.0

cheapr turned multi-threaded, and its next stop is a C++20 public API.

◆ Current state

cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.

◆ Where it's heading

Two arcs run at once. The visible one is parallelism: what began as single-threaded C shortcuts is becoming a threaded compute layer, and the notes state the C/C++ API is mid-rewrite with a stable form promised at 2.0.0 behind a C++20 requirement. The quieter one is R C API compliance — 1.5.1 removed R_MissingArg, R_UnboundValue, Rf_findVar and Rf_findVarinFrame, the non-API entry points being closed off upstream. The 1.5.x patches since are narrow crash fixes, which reads as consolidation before the 2.0.0 break.

◆ Prediction

Expect 2.0.0 to land the stable C/C++ API behind a C++20 toolchain floor, with more of the existing function surface threaded in the interim. The package has announced both moves in its own release notes.

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.

Alternatives to cheapr and collapse

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 cheapr or collapse.

See all cheapr alternatives → · See all collapse alternatives →

Recent activity from cheapr and collapse

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

  1. 1mo agocheaprrep_len_ crash on shrinking lengths fixed
  2. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  3. 4mo agocheaprNon-API R internals removed
  4. 4mo agocheaprParallelised math, thread control, and a C API rewrite
  5. 7mo agocollapseNegative zero now hashes equal to zero across the package
  6. 8mo agocollapsecollap() no longer double-aggregates external weights
  7. 9mo agocollapseCustom unlist() preserves attributes
  8. 0y agocollapseAssorted bug fixes
  9. 1y agocheaprSubsetting speedups; sset_col negative-index crash fixed
  10. 1y agocheaprdf_modify added; attribute helpers renamed for intent
  11. 1y agocheaprcounts and str_coalesce added; reconstruct renamed to rebuild
  12. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up

Frequently asked questions

What is the difference between cheapr and collapse?

Both compete on the same themes — performance, simd, r-package — within Analytics. cheapr and collapse 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 cheapr better than collapse?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cheapr and collapse 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 cheapr?

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

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.