TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of arcgisutils and fastglm — release velocity, themes, recent moves, and the top alternatives to consider.
The R-ArcGIS plumbing layer grew a portal administration API and geoprocessing job support.
arcgisutils is the foundation of the R interface to ArcGIS — token handling, standardized httr2 request construction, and conversion between Esri JSON and R types for the packages built on top of it. Version 0.4.0 in October 2025 broadened it well past that role, adding functions to enumerate a portal's federated servers, users and resources, search content with automatic pagination, and submit geoprocessing jobs through new S7 classes. Token management has been on its current footing since 0.2.0, which moved tokens into an internal environment supporting multiple named keys.
A fast GLM solver stops being one function and becomes a count-model family
fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.
arcgisutils is the foundation of the R interface to ArcGIS — token handling, standardized httr2 request construction, and conversion between Esri JSON and R types for the packages built on top of it. Version 0.4.0 in October 2025 broadened it well past that role, adding functions to enumerate a portal's federated servers, users and resources, search content with automatic pagination, and submit geoprocessing jobs through new S7 classes. Token management has been on its current footing since 0.2.0, which moved tokens into an internal environment supporting multiple named keys.
The package is expanding from request plumbing into direct coverage of the ArcGIS Enterprise administrative and geoprocessing surface, which is a different kind of work from what it existed to support. Much of the new surface is marked experimental, so the shape is still being settled. Alongside the expansion runs steady API tidying — three deprecations and two functions removed outright in the same release, one of which dropped the dbplyr dependency.
The experimental sharing-API and URL-parsing functions are the most likely to change or firm up next, and the geoprocessing classes suggest job execution will be built out further. Given this package sits beneath arcgislayers, the deprecations introduced here will need a corresponding pass downstream.
fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.
The package changed what it is. Through 0.0.3 it was a drop-in replacement for glm() competing on speed; from 0.1.0 it targets the models people leave base R for — MASS::glm.nb, pscl::hurdle, pscl::zeroinfl — and reimplements their full estimation loops natively. The 0.1.1 follow-up is consolidation on that new surface: Firth generalised past binomial logit, SQUAREM acceleration on the zero-inflation EM driver, and a run of clamping guards and initialization fixes on the families most prone to overflow.
The numerical-stability work in 0.1.1 clusters on Tweedie and the inverse and sqrt link families, which suggests those paths are the newest and least exercised — expect further correctness fixes there before new model types.
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 arcgisutils or fastglm.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
College football's open data client hit v2 — and now reports how many API calls you have left.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all arcgisutils alternatives → · See all fastglm alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. arcgisutils and fastglm 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. arcgisutils and fastglm 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 arcgisutils alternatives in Analytics are ranked by recent ship velocity. Browse the "arcgisutils alternatives" section above for the current picks, or visit /alternatives/arcgisutils for the full list with editorial commentary on each.
Top fastglm alternatives in Analytics are ranked by recent ship velocity. Browse the "fastglm alternatives" section above for the current picks, or visit /alternatives/fastglm for the full list with editorial commentary on each.