STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of sdsfun and soilDBdata — release velocity, themes, recent moves, and the top alternatives to consider.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
soilDBdata exists so soilDB's tests can run without a NASIS connection.
soilDBdata is a data-only package supplying NASIS and gSSURGO sample datasets as .sqlite assets, installed separately by soilDB's GitHub Actions so unit tests that would otherwise need database access can run. It began as a proof of concept carrying MT663 pedon and component tables used in soil survey coursework, and its most recent release adds a Marshall Islands FY26 gSSURGO dataset. Releases are infrequent and driven by what the parent package needs to test.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
soilDBdata is a data-only package supplying NASIS and gSSURGO sample datasets as .sqlite assets, installed separately by soilDB's GitHub Actions so unit tests that would otherwise need database access can run. It began as a proof of concept carrying MT663 pedon and component tables used in soil survey coursework, and its most recent release adds a Marshall Islands FY26 gSSURGO dataset. Releases are infrequent and driven by what the parent package needs to test.
Development follows soilDB rather than leading it: assets get bumped when a soilDB version changes, and purpose lists are updated when soilDB adds a table. The one release that changed what testing is possible was v0.1.1, which added selected-set _View_1 tables alongside whole tables so both SS=TRUE and SS=FALSE code paths could be exercised. Four-year gaps between releases are normal here and do not indicate abandonment — a fixture package only needs to move when the fixtures go stale.
The recent addition is a new geography rather than a new table structure, so further releases most likely continue broadening dataset coverage as soilDB gains regions to test against.
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 sdsfun or soilDBdata.
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 sdsfun alternatives → · See all soilDBdata alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. sdsfun and soilDBdata 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. sdsfun and soilDBdata 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 sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.
Top soilDBdata alternatives in Analytics are ranked by recent ship velocity. Browse the "soilDBdata alternatives" section above for the current picks, or visit /alternatives/soildbdata for the full list with editorial commentary on each.