n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of cheapr and tmap — release velocity, themes, recent moves, and the top alternatives to consider.
cheapr turned multi-threaded, and its next stop is a C++20 public API.
cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.
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.
cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.
Two arcs run at once. The visible one is parallelism: what began as single-threaded C shortcuts is becoming a threaded compute layer, and the notes state the C/C++ API is mid-rewrite with a stable form promised at 2.0.0 behind a C++20 requirement. The quieter one is R C API compliance — 1.5.1 removed R_MissingArg, R_UnboundValue, Rf_findVar and Rf_findVarinFrame, the non-API entry points being closed off upstream. The 1.5.x patches since are narrow crash fixes, which reads as consolidation before the 2.0.0 break.
Expect 2.0.0 to land the stable C/C++ API behind a C++20 toolchain floor, with more of the existing function surface threaded in the interim. The package has announced both moves in its own release notes.
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 cheapr or tmap.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. cheapr 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. cheapr 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 cheapr alternatives in Analytics are ranked by recent ship velocity. Browse the "cheapr alternatives" section above for the current picks, or visit /alternatives/cheapr-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.