dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of statsmodels and Apache Superset — release velocity, themes, recent moves, and the top alternatives to consider.
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
Superset's tracked feed is a Helm chart tag stream with no notes attached.
The feed being tracked carries Apache Superset's Helm chart releases rather than Superset itself. Six chart versions landed between mid-July and 10 August, walking 0.21.x up to 0.22.5, and every entry carries only the project's boilerplate one-line description. What actually changed in any given chart bump is not disclosed in the feed.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
The feed being tracked carries Apache Superset's Helm chart releases rather than Superset itself. Six chart versions landed between mid-July and 10 August, walking 0.21.x up to 0.22.5, and every entry carries only the project's boilerplate one-line description. What actually changed in any given chart bump is not disclosed in the feed.
Chart releases are arriving roughly weekly, which points to steady packaging maintenance underneath — image bumps, template corrections, values-file changes — rather than a visible product push. Because the feed publishes no notes, the deployment layer is the only Superset surface observable here. Anyone tracking application-level work needs the core repository, not this stream.
The cadence supports exactly one confident call: more chart point releases within weeks. The entries carry no content indicating what those bumps will contain.
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 statsmodels or Apache Superset.
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.
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
Shiny made reactive apps observable, then gave them a way to tear themselves down
See all statsmodels alternatives → · See all Apache Superset 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 statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.
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/superset for the full list with editorial commentary on each.