tidyr
tidyr replaced separate() with a family that says what it does.
A side-by-side editorial comparison of Apache Superset and performance — release velocity, themes, recent moves, and the top alternatives to consider.
Superset's feed tracks Helm chart tags, so the BI product itself stays invisible here.
Every entry in this feed is a Helm chart tag from the apache/superset repository, carrying no notes beyond a one-line project blurb. The chart has moved from 0.19.0 to 0.22.5 in about six weeks, a packaging cadence rather than an application one. Nothing here describes a change to Superset's dashboards, SQL Lab, or semantic layer.
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.
Every entry in this feed is a Helm chart tag from the apache/superset repository, carrying no notes beyond a one-line project blurb. The chart has moved from 0.19.0 to 0.22.5 in about six weeks, a packaging cadence rather than an application one. Nothing here describes a change to Superset's dashboards, SQL Lab, or semantic layer.
The chart is being cut on a fast, small-increment schedule — five patches inside 0.22.x in under three weeks. That pattern usually reflects deployment plumbing being tuned against a moving upstream image rather than any single problem being chased. Until the crawl points at the release notes for Superset itself, this feed will keep reporting packaging motion and nothing about the product.
Expect continued 0.22.x patch tags at a similar pace, with a 0.23.0 chart bump likely when the next Superset application release lands. The entries themselves will stay note-free unless the project starts populating chart release bodies.
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.
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.
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.
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 Apache Superset or performance.
tidyr replaced separate() with a family that says what it does.
modeltime built conformal intervals in, then went quiet on features.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all Apache Superset alternatives → · See all performance alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Apache Superset 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. Apache Superset 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.
Top Apache Superset alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache Superset alternatives" section above for the current picks, or visit /alternatives/apache-superset for the full list with editorial commentary on each.
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.