rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
cheapr vs distributional
A side-by-side editorial comparison of cheapr and distributional — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
cheapr vs distributional: 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 distributional?
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
cheapr vs distributional: 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.
distributional
0.0ANALYTICS
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
◆ Current state
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
◆ Where it's heading
The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.
◆ Prediction
Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.
Alternatives to cheapr and distributional
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 distributional.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all cheapr alternatives → · See all distributional alternatives →
Recent activity from cheapr and distributional
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agocheaprrep_len_ crash on shrinking lengths fixed
- 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
- 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators ⚡
- 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
- 4mo agocheaprNon-API R internals removed
- 4mo agocheaprParallelised math, thread control, and a C API rewrite ⚡
- 5mo agodistributionalDirichlet and Horseshoe distributions added
- 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
- 1y agocheaprSubsetting speedups; sset_col negative-index crash fixed
- 1y agocheaprdf_modify added; attribute helpers renamed for intent
- 1y agocheaprcounts and str_coalesce added; reconstruct renamed to rebuild
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
Frequently asked questions
What is the difference between cheapr and distributional?
Both compete on the same themes — r-package — within Analytics. cheapr and distributional 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 distributional?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cheapr and distributional 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 distributional?
Top distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-r for the full list with editorial commentary on each.