Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
Comparison · Analytics
Holistics vs modelbased
A side-by-side editorial comparison of Holistics and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
Holistics vs modelbased: at a glance
What is Holistics?
Holistics keeps fencing in the AI layer it spent the summer building.
Holistics ships small, frequent notes - often one or two sentences - across three strands: AI features in Explore and Chat, as-code control of presentation through AML, and workspace hygiene like file history and dark mode. The August entries are entirely about the AI layer's edges rather than its capabilities: an AI user attribute for restricting what the assistant can reach, and now redaction of the data it is allowed to see. Bodies are frequently a single line, so scope has to be read from the headline and the release-note URL.
What is modelbased?
modelbased is turning marginal effects into a full contrast grammar
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
Holistics vs modelbased: editorial side-by-side
Holistics
5.0ANALYTICS
Holistics keeps fencing in the AI layer it spent the summer building.
◆ Current state
Holistics ships small, frequent notes - often one or two sentences - across three strands: AI features in Explore and Chat, as-code control of presentation through AML, and workspace hygiene like file history and dark mode. The August entries are entirely about the AI layer's edges rather than its capabilities: an AI user attribute for restricting what the assistant can reach, and now redaction of the data it is allowed to see. Bodies are frequently a single line, so scope has to be read from the headline and the release-note URL.
◆ 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, then access control with an AI-specific user attribute, and now field-level redaction. Access control decides which rows the assistant can reach; redaction decides what it may see inside them - the same governance thread at finer grain. Alongside it, Holistics keeps pulling presentation into AML - custom charts, theme palettes, currency formats - so what analysts used to click is versioned as code.
◆ Prediction
With reach and visibility both now constrained, the remaining gap is accountability - logging what the assistant answered against which data - though the one-line release notes rarely signal scope far enough ahead to read the next step confidently.
modelbased
0.0ANALYTICS
modelbased is turning marginal effects into a full contrast grammar
◆ Current state
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
◆ Where it's heading
The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.
◆ Prediction
With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.
Alternatives to Holistics and modelbased
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 modelbased.
RStudio
RStudio ships through release branches, and the notes are commit messages
dbt Core
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Dovetail
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
tulpa
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
See all Holistics alternatives → · See all modelbased alternatives →
Recent activity from Holistics and modelbased
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3d agoHolisticsAI user attribute restricts AI access to sensitive data
- 3d agoHolisticsRedact data exposed to the AI assistant
- 17d agoHolisticsCustom currency and unit formats, per field
- 20d agoHolisticsFile history: per-file version timeline and restore
- 23d agoHolisticsCustom charts become AML code with GUI authoring
- 24d agoHolisticsColor palettes can be assigned at the theme level
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 6mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
Frequently asked questions
What is the difference between Holistics and modelbased?
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 modelbased?
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 modelbased?
Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.