dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
A side-by-side editorial comparison of Apache Superset and silx — 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.
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.
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.
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 Apache Superset 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 Apache Superset 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. Apache Superset is currently shipping more aggressively (velocity 5.0 vs 2.5), 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 2.5), 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 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.