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Comparison · Analytics
ApexCharts vs spmodel
A side-by-side editorial comparison of ApexCharts and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
ApexCharts vs spmodel: at a glance
What is ApexCharts?
Licensing settled, ApexCharts is back to changing what a chart can take as input.
ApexCharts is deep into a fast v6 line, shipping roughly weekly. The licensing arc that dominated 6.5 through 6.7 — trial watermarks, the first premium-gated chart type, then entitlement checks — has settled, and the last three releases are library work again. 6.9.0 is the largest of them: a histogram type that bins raw samples, a morph engine that conserves marks across chart types, and the end of the library's dependency-free packaging.
What is spmodel?
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
ApexCharts vs spmodel: editorial side-by-side
ApexCharts
10.0ANALYTICS
Licensing settled, ApexCharts is back to changing what a chart can take as input.
◆ Current state
ApexCharts is deep into a fast v6 line, shipping roughly weekly. The licensing arc that dominated 6.5 through 6.7 — trial watermarks, the first premium-gated chart type, then entitlement checks — has settled, and the last three releases are library work again. 6.9.0 is the largest of them: a histogram type that bins raw samples, a morph engine that conserves marks across chart types, and the end of the library's dependency-free packaging.
◆ Where it's heading
The through-line now is input and arrangement rather than catalogue size. Charts increasingly accept the measurements a team actually has instead of pre-aggregated values, and the seams that let you hand a chart its own layout — plotOptions.unit.positions, the pluggable layout hook — are being filled in with kits rather than hard-coded options. The premium boundary has stopped moving; the free catalogue keeps growing around it.
◆ Prediction
Expect the raw-observation pattern to reach another chart type now that the bar pathway handles binning, and expect the remaining pluggable seams to get companion kits the way positions just did.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
◆ Where it's heading
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
◆ Prediction
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
Alternatives to ApexCharts and spmodel
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 ApexCharts or spmodel.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
silx
silx settles into maintenance a release after its PySide6 migration
Plotly
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
See all ApexCharts alternatives → · See all spmodel alternatives →
Recent activity from ApexCharts and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoApexChartsUnit charts get a 39-shape companion kit
- 2d agoApexChartsHistogram bins raw samples; charts morph between types ⚡
- 9d agoApexChartsPer-data-point label offsets land as functions
- 10d agoApexChartsPie and donut slice clicks work again after a 6.7.0 regression
- 17d agoApexChartsSunburst charts arrive; premium features now need an entitled plan ⚡
- 22d agoApexChartsUnit chart is the first premium-gated chart type ⚡
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
Frequently asked questions
What is the difference between ApexCharts and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. ApexCharts is currently shipping more aggressively (velocity 10.0 vs 0.0), with 3 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.
Is ApexCharts better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ApexCharts is currently shipping more aggressively (velocity 10.0 vs 0.0), with 3 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.
What are the best alternatives to ApexCharts?
Top ApexCharts alternatives in Analytics are ranked by recent ship velocity. Browse the "ApexCharts alternatives" section above for the current picks, or visit /alternatives/apexcharts for the full list with editorial commentary on each.
What are the best alternatives to spmodel?
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.