STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of arcgisutils and TidyDensity — 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 distribution catalogue that grows by one family at a time, and rarely breaks anything.
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
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.
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.
The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.
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 TidyDensity.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all arcgisutils alternatives → · See all TidyDensity alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. arcgisutils and TidyDensity 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 TidyDensity 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 TidyDensity alternatives in Analytics are ranked by recent ship velocity. Browse the "TidyDensity alternatives" section above for the current picks, or visit /alternatives/tidydensity for the full list with editorial commentary on each.