ggpointless
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
A side-by-side editorial comparison of Kinsta and modsem — release velocity, themes, recent moves, and the top alternatives to consider.
Kinsta is moving MyKinsta's controls into its API, one surface per month
Kinsta's feed is a blog, so releases arrive as truncated posts, but the pattern underneath is consistent: management surfaces that used to require the MyKinsta dashboard keep reappearing in the Kinsta API. Domains, HTTPS, logs, and backups moved in July; visitor analytics — user agents, browsers, request origins — followed in August. Around that sits a year of bot-traffic work and a file manager in the dashboard, and the newest post extends resilience past backups into a named disaster-recovery offering.
modsem is grinding latent interaction models toward Mplus parity, one estimator at a time.
modsem fits interaction and quadratic effects between latent variables in R, offering both product-indicator approaches (modsem_pi) and distribution-analytic ones (modsem_da, covering LMS and QML). Releases land roughly monthly and are dense pull-request lists. The recent line is dominated by the LMS approach: gradient refactors, parallel E-steps, composite construct support, and careful handling of residual covariances between latent variables.
Kinsta's feed is a blog, so releases arrive as truncated posts, but the pattern underneath is consistent: management surfaces that used to require the MyKinsta dashboard keep reappearing in the Kinsta API. Domains, HTTPS, logs, and backups moved in July; visitor analytics — user agents, browsers, request origins — followed in August. Around that sits a year of bot-traffic work and a file manager in the dashboard, and the newest post extends resilience past backups into a named disaster-recovery offering.
The direction is toward WordPress hosting that can be operated entirely programmatically, with MyKinsta as one client among others rather than the control plane. Bot handling and now disaster recovery show the second thread: absorbing operational risk customers would otherwise manage themselves. The blog format hides scope — most posts are teasers — so direction is readable here but the size of any single release is not.
Expect the next API release to pick off another MyKinsta-only surface on the same roughly monthly rhythm, with the file manager the obvious candidate. How far disaster recovery goes beyond scheduled backups is the open question these posts do not answer.
modsem fits interaction and quadratic effects between latent variables in R, offering both product-indicator approaches (modsem_pi) and distribution-analytic ones (modsem_da, covering LMS and QML). Releases land roughly monthly and are dense pull-request lists. The recent line is dominated by the LMS approach: gradient refactors, parallel E-steps, composite construct support, and careful handling of residual covariances between latent variables.
Two things are being closed at once. The modelling gap — composites and formative constructs, categorical estimators, residual covariances in every direction, multigroup and clustered designs — brings modsem toward what commercial Mplus users expect, and the package's Mplus bridge is maintained alongside it, now with unique file IDs and a cleanup argument. The performance gap is the other: memoised H0, parallel E-step, optimized gradients and Hessians for both LMS and QML, all aimed at the distribution-analytic estimators that are expensive by construction. Convention borrowing from lavaan continues in message formatting and standard-error defaults.
The 1.0.20 and 1.0.21 releases both spent effort on residual covariances between endogenous and exogenous latent variables across estimation, prediction and standardization, and that thread has not obviously closed. The arrival of a second contributor moving MplusAutomation to Suggests suggests dependency trimming continues.
Other Infra & APIs 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 Kinsta or modsem.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveycore declared its API stable with every survey design type covered.
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
prospectr spent its biggest release in years fixing spectra it had been quietly mangling.
See all Kinsta alternatives → · See all modsem alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Kinsta 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Kinsta 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 Infra & APIs products to evaluate alongside.
Top Kinsta alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Kinsta alternatives" section above for the current picks, or visit /alternatives/kinsta for the full list with editorial commentary on each.
Top modsem alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "modsem alternatives" section above for the current picks, or visit /alternatives/modsem for the full list with editorial commentary on each.