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Basedash vs performance

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

Basedash vs performance: at a glance

FeatureBasedashperformance
SectorAnalyticsAnalytics
Velocity score7.50.0
Sparks · 30d10
Top themesbi, ai-analyst, external-sharing, apir-language, model-diagnostics, bayesian, easystats
Last editorial update1h ago7d ago
WebsiteVisit →Visit →

What is Basedash?

Basedash keeps pushing its data out of the workspace — now to people without accounts

Basedash is a BI tool built around an AI data analyst, and the last month has been about getting its output to more places: an API that exposes chat, insights, automations and dashboards; scheduled snapshots to email and Slack; and now a link that opens a live, filterable dashboard for someone with no Basedash account. Alongside that distribution work sits a research-preview agent, Tasks, that reads company data and produces a ranked to-do list. Audit logs, including a record of every query the AI runs, arrived in the same window.

Read the full Basedash trajectory →

What is performance?

performance keeps adding ways to check a model you have already fitted.

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

Read the full performance trajectory →

Basedash vs performance: editorial side-by-side

B
Basedash
ANALYTICS
7.5

Basedash keeps pushing its data out of the workspace — now to people without accounts

◆ Current state

Basedash is a BI tool built around an AI data analyst, and the last month has been about getting its output to more places: an API that exposes chat, insights, automations and dashboards; scheduled snapshots to email and Slack; and now a link that opens a live, filterable dashboard for someone with no Basedash account. Alongside that distribution work sits a research-preview agent, Tasks, that reads company data and produces a ranked to-do list. Audit logs, including a record of every query the AI runs, arrived in the same window.

◆ Where it's heading

Two arcs are running in parallel. One narrows the gap between viewing data and acting on it — suggestions before you type a prompt, then Tasks writing the work item and tracking whether the metric moved. The other decouples consumption from seats: API, subscriptions, and public links each reach an audience that never logs in. The interface work (module-anchored sidebar, per-user table sorting that doesn't rewrite the author's SQL) reads as load-bearing for both.

◆ Prediction

Tasks leaving research preview is the release that decides how much of this is real; its value depends entirely on the outcome-tracking loop having run long enough to show whether its recommendations worked. Expect the sharing surface to grow permissions and expiry controls next, since a link that works without an account is the first place governance pressure lands.

P
performance
ANALYTICS
0.0

performance keeps adding ways to check a model you have already fitted.

◆ Current state

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

◆ Where it's heading

Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.

◆ Prediction

With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.

Alternatives to Basedash and performance

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 performance.

See all Basedash alternatives → · See all performance alternatives →

Recent activity from Basedash and performance

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

  1. 2d agoBasedashIntroducing public sharing: live dashboards for anyone
  2. 5d agoBasedashIntroducing Tasks: your operations, on autopilot
  3. 6d agoBasedashA sidebar that follows what you’re working on
  4. 12d agoBasedashIntroducing Basedash Subscriptions
  5. 13d agoBasedashSort and arrange tables without changing the chart
  6. 19d agoBasedashIntroducing Basedash audit logs
  7. 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
  8. 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
  9. 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
  10. 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
  11. 10mo agoperformanceFixes CRAN checks after an rstanarm update
  12. 11mo agoperformancetinytable output format in display()

Frequently asked questions

What is the difference between Basedash and performance?

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 performance?

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 performance?

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