dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of OpenHouse and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
OpenHouse ships continuously — five releases in the twelve days covered here — with each tag carrying a single merged pull request. The substantive recent work sits in two areas: table governance, where CREATE OR REPLACE AS SELECT was silently dropping retention, replication, history and PII column tags, and operability, where the DataLoader gained a typed exception hierarchy with per-request IDs and the scheduler gained targeted log tokens. Table feature toggles also picked up self-service overrides that let table owners opt in to a feature the server has not ramped.
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.
OpenHouse ships continuously — five releases in the twelve days covered here — with each tag carrying a single merged pull request. The substantive recent work sits in two areas: table governance, where CREATE OR REPLACE AS SELECT was silently dropping retention, replication, history and PII column tags, and operability, where the DataLoader gained a typed exception hierarchy with per-request IDs and the scheduler gained targeted log tokens. Table feature toggles also picked up self-service overrides that let table owners opt in to a feature the server has not ramped.
The project is at the stage where correctness at the edges matters more than new surface: policies surviving a replace, auth failures not being retried as if they were transient, scheduler decisions being greppable in production logs. The observability work is explicitly phased, with OTEL gauges and DLQ counters deferred to a later step, so instrumentation is being staged rather than dropped in at once. The pattern of one PR per release tag means the feed reads as a commit log and the meaningful changes have to be picked out of dependency bumps.
Phase 2 of the jobs observability plan — OTEL gauges, a heartbeat sampler, and dead-letter-queue counters — is named in the notes as deferred and is the most likely next substantive change.
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 OpenHouse or statsmodels.
DoWhy adds one estimation method a year and keeps its identification edge.
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
ggplot2 swapped its object system out from under a decade of downstream code
See all OpenHouse 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. OpenHouse 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. OpenHouse 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 OpenHouse alternatives in Analytics are ranked by recent ship velocity. Browse the "OpenHouse alternatives" section above for the current picks, or visit /alternatives/openhouse 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.