compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
A side-by-side editorial comparison of libr and nabla — release velocity, themes, recent moves, and the top alternatives to consider.
The SAS datastep clone for R just got roughly nineteen times faster.
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
nabla dropped its C++ engine to chase exact derivatives at any order.
nabla does forward-mode automatic differentiation in R using dual numbers, returning derivatives exact to machine precision rather than approximated by finite differences. It shipped as dualr in January 2026, then a day later released 0.5.0 under a changed identity: derivatives generalise from a hardcoded second order to arbitrary order through recursive nesting, and the Rcpp and C++ fast paths are deleted so the package is pure R. The current release, 0.7.1, is CRAN resubmission cleanup.
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
Two threads run through these entries — steady correctness work on SAS file import, and a much less frequent but far more consequential push on making datastep() viable at real data volumes. The recent fix to empty-variable typing suggests the sas7bdat reader is still where edge cases surface. Having addressed both speed and package size in one release, the obvious remaining pressure is correctness and coverage of SAS semantics rather than throughput.
Expect the next releases to continue narrowing sas7bdat import edge cases, with any further datastep() work aimed at supporting more SAS syntax rather than at speed.
nabla does forward-mode automatic differentiation in R using dual numbers, returning derivatives exact to machine precision rather than approximated by finite differences. It shipped as dualr in January 2026, then a day later released 0.5.0 under a changed identity: derivatives generalise from a hardcoded second order to arbitrary order through recursive nesting, and the Rcpp and C++ fast paths are deleted so the package is pure R. The current release, 0.7.1, is CRAN resubmission cleanup.
The 0.5.0 release note states the positioning explicitly: exact machine-precision derivatives at any order, not speed. Removing compiled code to make that claim coherent is an unusual direction, most numerical R packages move the other way, and it commits the package to a niche where correctness beats throughput. The old second-order API survives as deprecated thin wrappers, so the pivot was made without stranding early users. The rapid rename and version jump suggest identity was settled late.
Expect CRAN acceptance to be followed by work on the optimiser and MLE integration paths, where arbitrary-order derivatives have the clearest use.
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 libr or nabla.
An MLE package rebuilt around composable solvers, then renamed to match.
Eight months from first release to keyring caching and workload identity.
A research-project workflow package where the interesting work is in the plumbing.
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
A package retired in 2017 just got rewritten against R's public C API.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. libr is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. libr is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top libr alternatives in Analytics are ranked by recent ship velocity. Browse the "libr alternatives" section above for the current picks, or visit /alternatives/libr for the full list with editorial commentary on each.
Top nabla alternatives in Analytics are ranked by recent ship velocity. Browse the "nabla alternatives" section above for the current picks, or visit /alternatives/nabla for the full list with editorial commentary on each.