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DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of Apache Superset and statsmodels — 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.
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.
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.
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.
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 statsmodels.
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 Apache Superset alternatives → · See all statsmodels 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 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.