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Comparison · Analytics

Basedash vs hstats

A side-by-side editorial comparison of Basedash and hstats — release velocity, themes, recent moves, and the top alternatives to consider.

Basedash vs hstats: at a glance

FeatureBasedashhstats
SectorAnalyticsAnalytics
Velocity score7.50.0
Sparks · 30d10
Top themesai-analyst, prescriptive-analytics, embedded-bi, enterprise-controlsinteraction statistics, partial dependence, model explainability, r package
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is Basedash?

Basedash is done answering questions about your data — it now wants to tell you what to do next.

Basedash spent July and early August building the surfaces of an AI-native BI tool: suggestions that propose questions before you type, subscriptions that push dashboards to Slack and email, audit logs that record every query the AI runs, and a developer platform exposing the whole feature set through an API. Tasks, now in research preview, changes the output shape entirely — instead of charts and answers it produces a ranked list of work with a stated rationale and expected outcome, then watches whether the metrics move. A sidebar rebuild the day before quietly names the product's five pillars: Chat, Dashboards, Automations, Insights, and Data.

Read the full Basedash trajectory →

What is hstats?

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

Read the full hstats trajectory →

Basedash vs hstats: editorial side-by-side

B
Basedash
ANALYTICS
7.5

Basedash is done answering questions about your data — it now wants to tell you what to do next.

◆ Current state

Basedash spent July and early August building the surfaces of an AI-native BI tool: suggestions that propose questions before you type, subscriptions that push dashboards to Slack and email, audit logs that record every query the AI runs, and a developer platform exposing the whole feature set through an API. Tasks, now in research preview, changes the output shape entirely — instead of charts and answers it produces a ranked list of work with a stated rationale and expected outcome, then watches whether the metrics move. A sidebar rebuild the day before quietly names the product's five pillars: Chat, Dashboards, Automations, Insights, and Data.

◆ Where it's heading

The arc runs from self-serve querying toward prescription and closed-loop measurement. Each release chips away at the assumption that a human must decide what to look at: suggestions removed the blank prompt, subscriptions removed the visit, and Tasks removes the interpretation step. The navigation rework is the tell that this is now a multi-module product rather than a chat box with extras — and the enterprise scaffolding arriving alongside it, audit logs covering AI queries plus retention controls, is what makes an autonomous analyst deployable rather than a demo.

◆ Prediction

Tasks graduating from research preview will be the release to watch; the outcome-tracking loop it describes only has value once it has run long enough to show whether its recommendations worked. Expect Tasks to become a sixth sidebar module and to be exposed through the developer platform API, since that is where every other Basedash capability has landed.

H
hstats
ANALYTICS
0.0

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

◆ Current state

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

◆ Where it's heading

The structural work — the hstats_matrix object, quantile approximation, revised plotting — landed in 1.0.0 just outside this window, and nothing since has changed the package's shape. What continues is model-coverage plumbing: mlr3 classification modes, ranger survival behind a survival argument, and factor predictions added in 1.1.0 then removed again in 1.2.0. The most recent releases are compatibility-driven, tracking ggplot2 rather than the interaction statistics.

◆ Prediction

Expect the next release to be another dependency-compatibility pass or a new model backend working out of the box, rather than new interaction statistics.

Alternatives to Basedash and hstats

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 Basedash or hstats.

See all Basedash alternatives → · See all hstats alternatives →

Recent activity from Basedash and hstats

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 14h agoBasedashIntroducing Tasks: your operations, on autopilot
  2. 1d agoBasedashA sidebar that follows what you’re working on
  3. 7d agoBasedashIntroducing Basedash Subscriptions
  4. 8d agoBasedashSort and arrange tables without changing the chart
  5. 14d agoBasedashIntroducing Basedash audit logs
  6. 15d agoBasedashMotherDuck is now a supported data source
  7. 10mo agohstatsggplot 4.0 compatibility and test coverage
  8. 1y agohstatsranger survival models supported out of the box
  9. 2y agohstatsMoves to ModelOriented; factor predictions removed
  10. 2y agohstatsICE facets for multioutput models; mlr3 fixes
  11. 2y agohstatsFaster data.frame paths; NaN H-statistics fixed
  12. 2y agohstatsFactor predictions and line-style 2D partial dependence

Frequently asked questions

What is the difference between Basedash and hstats?

They serve adjacent needs but don't currently overlap on shipped themes. Basedash is currently shipping more aggressively (velocity 7.5 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 Basedash better than hstats?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Basedash is currently shipping more aggressively (velocity 7.5 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 Basedash?

Top Basedash alternatives in Analytics are ranked by recent ship velocity. Browse the "Basedash alternatives" section above for the current picks, or visit /alternatives/basedash for the full list with editorial commentary on each.

What are the best alternatives to hstats?

Top hstats alternatives in Analytics are ranked by recent ship velocity. Browse the "hstats alternatives" section above for the current picks, or visit /alternatives/hstats for the full list with editorial commentary on each.