silx
silx settles into maintenance a release after its PySide6 migration
A side-by-side editorial comparison of Plotly and r2dii.plot — release velocity, themes, recent moves, and the top alternatives to consider.
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
PACTA's climate-alignment charting layer split prep from plotting, then settled into stable.
r2dii.plot renders the standard PACTA climate-alignment charts — trajectory, tech mix, emission intensity — as ggplot2 objects, paired with the 2DII colour palettes and theme. Since 0.4.0 the package has exposed a two-step pipeline where prep_*() shapes the data before plot_*() draws it, while qplot_*() remains the one-call convenience path. It declared itself stable in early 2025.
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
The Cloud releases are assembling the standard pieces of a hosting business in order — identity first (domain verification, explicitly framed as the step before SSO), then billing (viewer seats, then metered compute credits), and now production-grade serving (custom domains, automatic certificate renewal). Studio is being hardened as the authoring front end that feeds it: Universal Deployment pushed beyond Dash apps, credentials saved once and reused, a Winget channel to widen Windows installs, and in v0.0.86 a rebuilt session engine plus automatic retries so agent runs survive expired tokens. The two tracks converge on one funnel — author in Studio, deploy to Cloud, pay by compute consumed.
The Domain Verification entry names SSO as the next step and places it in the Enterprise tier, so single sign-on is the most likely Cloud release next. Studio should hold its one-to-two-week cadence, with the newly added app thumbnails pointing toward more work on browsing and organizing generated apps.
r2dii.plot renders the standard PACTA climate-alignment charts — trajectory, tech mix, emission intensity — as ggplot2 objects, paired with the 2DII colour palettes and theme. Since 0.4.0 the package has exposed a two-step pipeline where prep_*() shapes the data before plot_*() draws it, while qplot_*() remains the one-call convenience path. It declared itself stable in early 2025.
The package has been converging on a settled contract for years. Early releases chased visual polish and label handling, then 0.2.0 exposed the palette scales as reusable ggplot2 components, and 0.4.0 made the prepared data a first-class artefact rather than something hidden inside a plotting call. Recent releases are documentation and hygiene: a data_dictionary describing every column, definitions filled in, demo datasets renamed to say they are demos. It also moved organisations, from 2DII to RMI-PACTA, and its releases stay pinned to r2dii.analysis and to ggplot2's deprecation schedule.
With the lifecycle marked stable and the last two releases confined to dataset naming and documentation, the next release is most likely another ggplot2 compatibility pass or a sibling-package alignment rather than new chart types.
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 Plotly or r2dii.plot.
silx settles into maintenance a release after its PySide6 migration
aniread stops asking you to know which tracker wrote the file
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
OpenCTI spends a release unblocking queues and hardening upserts
Mimir's feed is a weekly Helm bot, with the 3.2 candidate the only real release in months
See all Plotly alternatives → · See all r2dii.plot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Plotly 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. Plotly 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 Plotly alternatives in Analytics are ranked by recent ship velocity. Browse the "Plotly alternatives" section above for the current picks, or visit /alternatives/plotly for the full list with editorial commentary on each.
Top r2dii.plot alternatives in Analytics are ranked by recent ship velocity. Browse the "r2dii.plot alternatives" section above for the current picks, or visit /alternatives/r2dii-plot for the full list with editorial commentary on each.