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A side-by-side editorial comparison of Holistics and mlr3viz — release velocity, themes, recent moves, and the top alternatives to consider.
Holistics is adding governance to the AI layer it spent the summer building.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
The AI work has moved through a recognizable sequence: capability first with chart suggestions, then observability with AI Chat Insights for admins, and now access control with an AI-specific user attribute. Alongside it, Holistics keeps pulling presentation into AML - custom charts, theme palettes, currency formats - so the things analysts used to click are versioned as code. File history is the join between the two threads, giving every dashboard, model, and dataset its own restorable timeline.
With capability, visibility, and access control now in place for the AI layer, the next step is likely audit or policy depth - logging what the assistant answered against which data - rather than new AI surfaces.
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
The package is being narrowed toward generic plotting infrastructure while learner-specific plots migrate to the packages that own those learners. What it does add is access rather than new charts — passing parameters through to precrec::autoplot(), better hints when the wrong autoplot type is requested, and a confidence-interval plot for mlr3inferr. Determinism across ggplot2 versions has become a recurring concern, which is what happens when a visualization package is depended on by documentation and tests.
Following the Cox proportional-hazards precedent, further learner-specific plots are likely to move to their owning packages, leaving mlr3viz with the cross-cutting result objects.
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 Holistics or mlr3viz.
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Omni ships weekly, and almost every week the headline item is an AI feature.
silx settles into maintenance a release after its PySide6 migration
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread stops asking you to know which tracker wrote the file
Rho's release machinery finally produced a stable build — and it shipped no new product.
See all Holistics alternatives → · See all mlr3viz alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Holistics is currently shipping more aggressively (velocity 5.0 vs 2.5), with 0 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Holistics is currently shipping more aggressively (velocity 5.0 vs 2.5), with 0 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.
Top Holistics alternatives in Analytics are ranked by recent ship velocity. Browse the "Holistics alternatives" section above for the current picks, or visit /alternatives/holistics for the full list with editorial commentary on each.
Top mlr3viz alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3viz alternatives" section above for the current picks, or visit /alternatives/mlr3viz for the full list with editorial commentary on each.