silx
silx settles into maintenance a release after its PySide6 migration
A side-by-side editorial comparison of EpiNow2 and Holistics — release velocity, themes, recent moves, and the top alternatives to consider.
EpiNow2 unified its model interface, then went back to deepen the estimators behind it
EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.
Holistics is adding governance to the AI layer it spent the summer building.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.
The package spent this window paying down interface debt and is now extending from the tidier base. Options that existed only for `estimate_infections()` have been propagated outward: `estimate_truncation()` gained the full `dist_spec` delay families, `obs_opts()` observation model selection between Poisson and negative binomial, and the `likelihood` and `return_likelihood` settings that make prior-only fits and loo-compatible output possible. Hardcoded assumptions are being replaced by specifiable ones in the same motion — the truncation model's additive noise term was a fixed `sigma ~ normal(0, 1)` prior and is now a `dist_spec` argument.
Expect the remaining modelling functions to keep converging on the shared options interface, since the last two releases have each moved another function onto it. A new `estimate_dist()` for interval-censored linelist data suggests delay estimation is the area still gaining surface.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
The AI work has moved through a recognizable sequence: capability first with chart suggestions, then observability with AI Chat Insights for admins, and now access control with an AI-specific user attribute. Alongside it, Holistics keeps pulling presentation into AML - custom charts, theme palettes, currency formats - so the things analysts used to click are versioned as code. File history is the join between the two threads, giving every dashboard, model, and dataset its own restorable timeline.
With capability, visibility, and access control now in place for the AI layer, the next step is likely audit or policy depth - logging what the assistant answered against which data - rather than new AI surfaces.
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 EpiNow2 or Holistics.
silx settles into maintenance a release after its PySide6 migration
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
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
See all EpiNow2 alternatives → · See all Holistics alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Holistics 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. Holistics 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 EpiNow2 alternatives in Analytics are ranked by recent ship velocity. Browse the "EpiNow2 alternatives" section above for the current picks, or visit /alternatives/epinow2 for the full list with editorial commentary on each.
Top Holistics alternatives in Analytics are ranked by recent ship velocity. Browse the "Holistics alternatives" section above for the current picks, or visit /alternatives/holistics for the full list with editorial commentary on each.