dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of OpenCTI and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
OpenCTI ships on a roughly weekly date-stamped cadence, and the last six releases divide cleanly: the connector catalog was redesigned into a faceted marketplace, then the surrounding integrations experience was reworked around it, then the platform gained two-way connection with Filigran's XTM Hub. Alongside that, saved searches and saved filters became shareable and reusable across dashboards. The most recent releases are weighted toward fixes rather than new surface.
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.
OpenCTI ships on a roughly weekly date-stamped cadence, and the last six releases divide cleanly: the connector catalog was redesigned into a faceted marketplace, then the surrounding integrations experience was reworked around it, then the platform gained two-way connection with Filigran's XTM Hub. Alongside that, saved searches and saved filters became shareable and reusable across dashboards. The most recent releases are weighted toward fixes rather than new surface.
The centre of gravity is moving from OpenCTI as a self-contained platform to OpenCTI as a client of Filigran's wider ecosystem — connectors sourced from a catalog with support tiers, custom views deployed from XTM Hub, an MCP server exposed through XTM One. The workflow engine is maturing in parallel, picking up draft approval, transition restrictions and full reset. Telemetry coverage expanded significantly in the same period, which is what makes the catalog's adoption measurable.
Expect more of the platform's configuration surface — dashboards, playbooks, mappers — to become distributable through XTM Hub the way custom views and connectors already are. The workflow approval features suggest governance controls are the next area to fill in.
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 OpenCTI 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 OpenCTI 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. OpenCTI is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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. OpenCTI is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 OpenCTI alternatives in Analytics are ranked by recent ship velocity. Browse the "OpenCTI alternatives" section above for the current picks, or visit /alternatives/opencti 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.