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Comparison · Analytics
distributional vs vellumplot
A side-by-side editorial comparison of distributional and vellumplot — release velocity, themes, recent moves, and the top alternatives to consider.
distributional vs vellumplot: at a glance
What is distributional?
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
What is vellumplot?
vellumplot tags its first release with a bet most R grammars don't make: the static figure and the widget are the same object.
A new grammar of graphics built on the vellum vector engine, developing fast — ten releases in roughly three weeks — and now at its first tagged release. The distinguishing architectural claim is that the compiled plot is the scene, so a static export and an interactive widget cannot drift apart, and that it renders without a graphics device because vellum measures text itself. Accessibility is treated as a first-class output rather than an afterthought: tagged PDF with a navigable structure tree and alt text, a plot_lint() check, and colour-vision-deficiency simulation at render time.
distributional vs vellumplot: editorial side-by-side
distributional
0.0ANALYTICS
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
◆ Current state
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
◆ Where it's heading
The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.
◆ Prediction
Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.
vellumplot
6.3ANALYTICS
vellumplot tags its first release with a bet most R grammars don't make: the static figure and the widget are the same object.
◆ Current state
A new grammar of graphics built on the vellum vector engine, developing fast — ten releases in roughly three weeks — and now at its first tagged release. The distinguishing architectural claim is that the compiled plot is the scene, so a static export and an interactive widget cannot drift apart, and that it renders without a graphics device because vellum measures text itself. Accessibility is treated as a first-class output rather than an afterthought: tagged PDF with a navigable structure tree and alt text, a plot_lint() check, and colour-vision-deficiency simulation at render time.
◆ Where it's heading
The release sequence shows a grammar filling in ggplot2-parity features and specialist marks in parallel. Parity work landed as secondary axes, rich legend titles, and Sankey styling; the specialist end added categorical datashading, image marks, flow maps and edge bundling for dense graphs. Version 0.7.0 shows a willingness to break early — vsunburst() was removed outright in favour of one vhierarchy() constructor covering sunburst, icicle, treemap and circlepack — which is the right time to do it and suggests the API is still being consolidated toward fewer, more general constructors.
◆ Prediction
Expect more consolidation of near-duplicate constructors under type arguments and continued expansion of the declarative interactivity introduced in 0.7.0, now that the first tagged release has fixed a public API surface.
Alternatives to distributional and vellumplot
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 distributional or vellumplot.
epiworldR
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
watina
A groundwater database client that has started doing the domain analysis too
inbospatial
A thin R wrapper over Flemish geospatial services, adding one standard at a time
Fluent Bit
Fluent Bit keeps two lines alive while the 5.x branch quietly opens 5.1.
OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
See all distributional alternatives → · See all vellumplot alternatives →
Recent activity from distributional and vellumplot
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 14d agovellumplotFirst tagged release: one spec compiles to PNG, SVG, tagged PDF and a widget ⚡
- 19d agovellumplotFlow maps and edge bundling for dense graph plots
- 24d agovellumplotvhierarchy() replaces vsunburst(); declarative interactivity arrives
- 26d agovellumplotSankey crossing minimisation and per-branch sunburst colouring
- 29d agovellumplotSecondary axes land; rich legend titles stop clipping
- 1mo agovellumplotCategorical datashading in one call, plus image marks at data points
- 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
- 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators ⚡
- 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
- 5mo agodistributionalDirichlet and Horseshoe distributions added
- 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
Frequently asked questions
What is the difference between distributional and vellumplot?
They serve adjacent needs but don't currently overlap on shipped themes. vellumplot is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is distributional better than vellumplot?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. vellumplot is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to distributional?
Top distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-r for the full list with editorial commentary on each.
What are the best alternatives to vellumplot?
Top vellumplot alternatives in Analytics are ranked by recent ship velocity. Browse the "vellumplot alternatives" section above for the current picks, or visit /alternatives/vellumplot for the full list with editorial commentary on each.