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Comparison · Analytics

bayesplot vs Countly

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

bayesplot vs Countly: at a glance

FeaturebayesplotCountly
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themesbayesian workflow, stan, posterior predictive checks, ggplot2 compatibilityproduct-analytics, self-hosted, security-hardening, sandboxing
Last editorial update57m ago9h ago
WebsiteVisit →Visit →

What is bayesplot?

bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.

bayesplot supplies the plotting layer for Stan-adjacent Bayesian workflows: posterior predictive checks, MCMC diagnostics and LOO diagnostics. Releases through 2025 alternate between new plot families and keeping pace with ggplot2, which changed behavior twice in the visible window. Contributions increasingly arrive from outside the core Stan team.

Read the full bayesplot trajectory →

What is Countly?

Countly's LTS line is spending its releases on hardening the surfaces customers extend.

The 25.03 LTS and 24.05 branches are moving together, and the recent content is dominated by security and scoping work rather than features. The latest LTS rebuilds the api and frontend Docker images as multi-stage builds on Debian 13 with Node 24 so compilers and build tooling no longer ship, overrides fourteen vulnerable transitive dependencies, and replaces the unmaintained v8-sandbox behind custom code with isolated-vm. Earlier releases scoped internal event hooks to their own apps, fixed the consents table returning fields beyond the consent columns, and stopped dashboard widgets being copied by users without access to the referenced apps.

Read the full Countly trajectory →

bayesplot vs Countly: editorial side-by-side

B
bayesplot
ANALYTICS
0.0

bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.

◆ Current state

bayesplot supplies the plotting layer for Stan-adjacent Bayesian workflows: posterior predictive checks, MCMC diagnostics and LOO diagnostics. Releases through 2025 alternate between new plot families and keeping pace with ggplot2, which changed behavior twice in the visible window. Contributions increasingly arrive from outside the core Stan team.

◆ Where it's heading

Two forces drive the release line: expanding what can be checked visually, and absorbing upstream ggplot2 churn. The 1.13-1.14 pair shows the first, adding LOO-PIT ECDF plots, quantile dot plots and discrete-data handling across the stat family, while 1.12 and 1.15 are largely spent on ggplot2 3.6 and 4.0 compatibility. The recurring new-contributor lists suggest maintenance load is being spread rather than concentrated.

◆ Prediction

Discrete-data support has rolled out plot family by plot family across three releases; the next release most likely continues that sweep and finishes the ggplot2 v4 adaptation.

C
Countly
ANALYTICS
5.0

Countly's LTS line is spending its releases on hardening the surfaces customers extend.

◆ Current state

The 25.03 LTS and 24.05 branches are moving together, and the recent content is dominated by security and scoping work rather than features. The latest LTS rebuilds the api and frontend Docker images as multi-stage builds on Debian 13 with Node 24 so compilers and build tooling no longer ship, overrides fourteen vulnerable transitive dependencies, and replaces the unmaintained v8-sandbox behind custom code with isolated-vm. Earlier releases scoped internal event hooks to their own apps, fixed the consents table returning fields beyond the consent columns, and stopped dashboard widgets being copied by users without access to the referenced apps.

◆ Where it's heading

The pattern across these releases is closing the gaps where a customer-supplied artefact — custom hook code, a copied widget, a projection on a request — could reach further than intended. That work is now touching the runtime itself, and the isolated-vm swap is a breaking change: custom code relying on setTimeout, setInterval or async completion fails with a logged error instead of running. The journey engine is the only place shipping genuinely new capability, and it is enterprise-only.

◆ Prediction

Expect follow-up releases to soften the custom-code migration, since the isolated-vm switch silently breaks any hook that awaited a timer, and further ab-testing work now that pystan has been replaced with compiled Stan executables.

Alternatives to bayesplot and Countly

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 bayesplot or Countly.

See all bayesplot alternatives → · See all Countly alternatives →

Recent activity from bayesplot and Countly

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

  1. 1d agoCountlyCustom-code sandbox swapped to isolated-vm; images rebuilt on Node 24
  2. 10d agoCountlyFixes for event keys containing special characters
  3. 10d agoCountlyJourney deeplinks take dynamic parameters; hooks validated on save
  4. 20d agoCountlyStar-rating logo path and data-manager transformation fixes
  5. 21d agoCountlyLTS backport: data-manager transformation fix
  6. 1mo agoCountlyJourneys survive user merges; SDK-provided asset paths
  7. 8mo agobayesplotmcmc_scatter gains shape; pre-ggplot2 v4 theme behavior restored
  8. 11mo agobayesplotQuantile dot plots and broader discrete-data support
  9. 1y agobayesplotppc_loo_pit_ecdf() added; KM overlays gain truncation control
  10. 1y agobayesplotggplot2 3.6 compatibility and a run of plot-data fixes
  11. 2y agobayesplotPatch caps ppc_pit_ecdf evaluation points at 1000
  12. 2y agobayesplotbins/breaks across histograms; all LOO plots accept psis_object

Frequently asked questions

What is the difference between bayesplot and Countly?

They serve adjacent needs but don't currently overlap on shipped themes. Countly 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 bayesplot better than Countly?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Countly 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 bayesplot?

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

What are the best alternatives to Countly?

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