HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of dataSDA and mize — release velocity, themes, recent moves, and the top alternatives to consider.
dataSDA grew from a dataset collection into a symbolic-data conversion toolkit.
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
A numerical optimization toolkit that has been feature-complete and quiet since 2017
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
The arc across this window runs from cataloguing to tooling. Early releases added datasets and then spent two consecutive releases fixing format documentation across all 105 of them. Later releases shift to functions: format converters, symbolic CSV I/O, and most recently a diagnostic that flags zero-width intervals before they reach tools that divide by interval width. That last addition is the clearest signal of intent — the package is starting to guard the analyses downstream of it, not just supply inputs.
Expect further validation helpers in the mould of the zero-width check, since interval data has several degenerate shapes that break downstream methods silently.
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
The pattern is a stable library rather than an abandoned one. Fixes address real reports - a bracket_step error when the Schmidt line search exhausts its function evaluation budget, an incorrect gradient count under backtracking with a specified step_down - and the maintainer used one release note to clarify that backtracking behaviour differs depending on whether step_down is supplied, which reads as answering a recurring question. The five and a half year gap between 0.2.4 and 0.2.5 is the clearest signal: the package is maintained on demand, not developed.
Expect nothing until an R or CRAN policy change forces another compliance patch, which is what triggered the most recent release.
Other Infra & APIs 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 dataSDA or mize.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
See all dataSDA alternatives → · See all mize alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. dataSDA is currently shipping more aggressively (velocity 2.5 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. dataSDA is currently shipping more aggressively (velocity 2.5 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 Infra & APIs products to evaluate alongside.
Top dataSDA alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "dataSDA alternatives" section above for the current picks, or visit /alternatives/datasda for the full list with editorial commentary on each.
Top mize alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mize alternatives" section above for the current picks, or visit /alternatives/mize for the full list with editorial commentary on each.