rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of collapse and tmap — release velocity, themes, recent moves, and the top alternatives to consider.
collapse got a JSS paper and a 7x fmean speedup in the same release.
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
Two years after a from-scratch rewrite, tmap is filling in the layers v4 promised.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.
Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
The extension mechanism introduced in 4.0 is where the interesting work is migrating: PMTiles support arrived through a separate experimental tmap.sources package, mode cycling became configurable via tmap_mode_pool() so packages like tmap.mapgl can register themselves, and shiny dispatch methods were added specifically to let other modes integrate. The core package is increasingly a rendering contract that satellite packages plug into.
Expect more rendering backends to land as sibling packages rather than in tmap itself, with the core continuing to absorb the dispatch and mode-management plumbing they need.
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 collapse or tmap.
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all collapse alternatives → · See all tmap alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. collapse and tmap 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. collapse and tmap 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 collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.
Top tmap alternatives in Analytics are ranked by recent ship velocity. Browse the "tmap alternatives" section above for the current picks, or visit /alternatives/tmap-r for the full list with editorial commentary on each.