dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of Fathom Analytics and silx — release velocity, themes, recent moves, and the top alternatives to consider.
Fathom rebuilds its query engine and bolts on Search Console, reaching for GA4's lunch.
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
The roadmap is clearly aimed at making Fathom a viable single-pane replacement for Google Analytics rather than a privacy-first complement to it. Expect continued investment in detection accuracy, reporting depth (custom exports, secondary dimensions), and Google-side integrations. The new analytics engine is foundational — it is what makes the next layer of features possible.
Next likely moves are deeper UTM and campaign analytics, an experimentation or goals-funnel surface, and tighter agency tooling that builds on self-serve site transfer and shared-dashboard exports.
silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.
The project is doing a generational refresh of its GUI layer: modern Qt binding, modules broken out of the composite widgets that had accumulated responsibilities, and the theming work that a desktop application needs to look current. Underneath, the recurring fixes are about HDF5 behavior in real facility environments — file locking, NFS refresh, Windows display paths — which is where a synchrotron toolkit actually gets stressed. Feature growth is concentrated in silx view rather than the library API.
Expect the 3.1.x line to keep filling in plotting options and theming, with the PySide6 default flushing out binding-specific bugs from downstream applications over the next few releases.
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 Fathom Analytics or silx.
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
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 Fathom Analytics alternatives → · See all silx alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. silx is currently shipping more aggressively (velocity 2.5 vs 1.3), 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. silx is currently shipping more aggressively (velocity 2.5 vs 1.3), 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 Fathom Analytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Fathom Analytics alternatives" section above for the current picks, or visit /alternatives/fathom-analytics for the full list with editorial commentary on each.
Top silx alternatives in Analytics are ranked by recent ship velocity. Browse the "silx alternatives" section above for the current picks, or visit /alternatives/silx for the full list with editorial commentary on each.