n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of fastplyr and RadialMR — release velocity, themes, recent moves, and the top alternatives to consider.
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.
RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
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.
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.
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.
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
This is a package being read closely by its maintainer rather than extended. The 1.2.x line pairs statistical corrections with defensive hardening — an rmr_format class check so unformatted input fails with a clear message, and plotly_radial() dispatching on object class instead of counting list elements. Both are the kind of change made while auditing, not while building.
Expect the audit to continue into the remaining estimator internals and print methods rather than new radial variants; the entries show no feature work queued.
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 fastplyr or RadialMR.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all fastplyr alternatives → · See all RadialMR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fastplyr and RadialMR 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastplyr and RadialMR 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.
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.
Top RadialMR alternatives in Analytics are ranked by recent ship velocity. Browse the "RadialMR alternatives" section above for the current picks, or visit /alternatives/radialmr for the full list with editorial commentary on each.