Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
Comparison · Analytics
Holistics vs weird
A side-by-side editorial comparison of Holistics and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Holistics vs weird: at a glance
What is Holistics?
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.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
Holistics vs weird: editorial side-by-side
Holistics
5.0ANALYTICS
Holistics is adding governance to the AI layer it spent the summer building.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to Holistics and weird
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 weird.
silx
silx settles into maintenance a release after its PySide6 migration
Plotly
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
See all Holistics alternatives → · See all weird alternatives →
Recent activity from Holistics and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2d agoHolisticsAI user attribute restricts AI access to sensitive data
- 16d agoHolisticsCustom currency and unit formats, per field
- 19d agoHolisticsFile history: per-file version timeline and restore
- 22d agoHolisticsCustom charts become AML code with GUI authoring
- 23d agoHolisticsColor palettes can be assigned at the theme level
- 27d agoHolisticsDate-range presets and typed shorthands
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between Holistics and weird?
They serve adjacent needs but don't currently overlap on shipped themes. Holistics is currently shipping more aggressively (velocity 5.0 vs 0.0), 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.
Is Holistics better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Holistics is currently shipping more aggressively (velocity 5.0 vs 0.0), 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.
What are the best alternatives to Holistics?
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.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.