tidyr
tidyr replaced separate() with a family that says what it does.
Comparison · Analytics
performance vs ggplot2
A side-by-side editorial comparison of performance and ggplot2 — release velocity, themes, recent moves, and the top alternatives to consider.
performance vs ggplot2: at a glance
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.
What is ggplot2?
ggplot2 swapped its object system out from under a decade of downstream code
The 4.0.0 release replaced ggplot2's S3 internals with S7 and made every geom's defaults settable from the theme, both breaking changes. The three releases since have been hotfixes cleaning up the fallout - regressions in geom_area(), position_stack() and the scale and guide systems - plus rlang interoperability repairs. The one genuinely new feature in that window is a quantile.type argument on boxplots.
performance vs ggplot2: editorial side-by-side
performance
0.0ANALYTICS
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.
ggplot2
0.0ANALYTICS
ggplot2 swapped its object system out from under a decade of downstream code
◆ Current state
The 4.0.0 release replaced ggplot2's S3 internals with S7 and made every geom's defaults settable from the theme, both breaking changes. The three releases since have been hotfixes cleaning up the fallout - regressions in geom_area(), position_stack() and the scale and guide systems - plus rlang interoperability repairs. The one genuinely new feature in that window is a quantile.type argument on boxplots.
◆ Where it's heading
This is the tail of a long-telegraphed migration: 3.5.2 existed largely to give downstream packages the is_*() predicates and accessor functions they would need before 4.0 landed. With theme(geom) and from_theme(), styling is consolidating into the theme rather than being repeated per layer, which is the direction the extension ecosystem now has to follow.
◆ Prediction
Expect further 4.0.x patches as S7-related regressions surface in extension packages, and more of the per-geom default surface to migrate into element_geom(). The entries give no indication of a 4.1 feature line yet.
Alternatives to performance and ggplot2
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 performance or ggplot2.
modeltime
modeltime built conformal intervals in, then went quiet on features.
cmdstanpy
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all performance alternatives → · See all ggplot2 alternatives →
Recent activity from performance and ggplot2
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
- 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
- 3mo agoggplot2Boxplots gain a quantile.type argument for SAS parity
- 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
- 6mo agoggplot2Interoperability fix across rlang versions
- 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
- 9mo agoggplot2Regression cleanup after the 4.0 rewrite
- 10mo agoperformanceFixes CRAN checks after an rstanarm update
- 11mo agoggplot2ggplot2 4.0 replaces S3 internals with S7 ⚡
- 11mo agoperformancetinytable output format in display()
- 1y agoggplot2Standardised class predicates to prepare packages for 4.0
- 2y agoggplot2Patterns and gradients in geom_sf, resolution() reverted
Frequently asked questions
What is the difference between performance and ggplot2?
They serve adjacent needs but don't currently overlap on shipped themes. performance and ggplot2 are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is performance better than ggplot2?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. performance and ggplot2 are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
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.
What are the best alternatives to ggplot2?
Top ggplot2 alternatives in Analytics are ranked by recent ship velocity. Browse the "ggplot2 alternatives" section above for the current picks, or visit /alternatives/ggplot2 for the full list with editorial commentary on each.