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Comparison · Analytics
cheapr vs fastplyr
A side-by-side editorial comparison of cheapr and fastplyr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
cheapr vs fastplyr: at a glance
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.
What is fastplyr?
A fast dplyr stand-in that keeps finding new places to skip work entirely.
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
cheapr vs fastplyr: editorial side-by-side
cheapr
0.0ANALYTICS
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.
fastplyr
0.0ANALYTICS
A fast dplyr stand-in that keeps finding new places to skip work entirely.
◆ Current state
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
◆ Where it's heading
The optimization strategy has shifted from making individual functions fast to reasoning about expressions before evaluating them — 0.9.9 began marking simple operators as group-unaware so expressions built only from them are evaluated across the whole data frame rather than per group. That is a structural bet: the package increasingly inspects what you wrote to decide how much work is actually needed. Running alongside it is a steady tightening of build requirements, with C++17, R 4.5.0 and CRAN's C API rules all landing within a year.
◆ Prediction
Expect the group-unaware classification to widen to more functions, since each addition compounds across every grouped expression, and expect the dependency floors to keep rising as the package tracks CRAN's compiled-code policy.
Alternatives to cheapr and fastplyr
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 fastplyr.
n1qn1c
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all cheapr alternatives → · See all fastplyr alternatives →
Recent activity from cheapr and fastplyr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agocheaprrep_len_ crash on shrinking lengths fixed
- 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
- 4mo agocheaprNon-API R internals removed
- 4mo agocheaprParallelised math, thread control, and a C API rewrite ⚡
- 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
- 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
- 1y agocheaprSubsetting speedups; sset_col negative-index crash fixed
- 1y agofastplyrf_mutate and f_reframe complete the verb set
- 1y agocheaprdf_modify added; attribute helpers renamed for intent
- 1y agocheaprcounts and str_coalesce added; reconstruct renamed to rebuild
- 1y agofastplyrDynamic argument evaluation and f_pull
- 1y agofastplyrf_fill added and grouped joins repaired
Frequently asked questions
What is the difference between cheapr and fastplyr?
Both compete on the same themes — r-package — within Analytics. cheapr and fastplyr 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 fastplyr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cheapr and fastplyr 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 fastplyr?
Top fastplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "fastplyr alternatives" section above for the current picks, or visit /alternatives/fastplyr for the full list with editorial commentary on each.