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cheapr vs gtsummary

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

Shared themes:r-package

cheapr vs gtsummary: at a glance

Featurecheaprgtsummary
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesperformance, parallelism, simd, c-apiclinical-tables, analysis-results-data, regression-summaries, reproducible-reporting
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 gtsummary?

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

Read the full gtsummary trajectory →

cheapr vs gtsummary: 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.

G
gtsummary
ANALYTICS
0.0

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

◆ Current state

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

◆ Where it's heading

The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.

◆ Prediction

Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.

Alternatives to cheapr and gtsummary

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 gtsummary.

See all cheapr alternatives → · See all gtsummary alternatives →

Recent activity from cheapr and gtsummary

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

  1. 1mo agocheaprrep_len_ crash on shrinking lengths fixed
  2. 2mo agogtsummaryTheme elements no longer evaluated by default
  3. 4mo agocheaprNon-API R internals removed
  4. 4mo agocheaprParallelised math, thread control, and a C API rewrite
  5. 8mo agogtsummaryARD strata functions and finer theme control
  6. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  7. 1y agocheaprSubsetting speedups; sset_col negative-index crash fixed
  8. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  9. 1y agocheaprdf_modify added; attribute helpers renamed for intent
  10. 1y agocheaprcounts and str_coalesce added; reconstruct renamed to rebuild
  11. 1y agogtsummaryData pre-processing restored after the 2.0 removal
  12. 1y agogtsummarytbl_merge gains explicit merge columns

Frequently asked questions

What is the difference between cheapr and gtsummary?

Both compete on the same themes — r-package — within Analytics. cheapr and gtsummary 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 gtsummary?

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

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