pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
Comparison · Infra & APIs
mice vs sits
A side-by-side editorial comparison of mice and sits — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
mice vs sits: at a glance
What is mice?
mice can finally predict, not just estimate, from multiply imputed data.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
What is sits?
An R package for satellite time series just grew a Python API.
sits classifies satellite image time series — building data cubes from cloud archives, training deep learning models on them, and producing land-cover maps. The releases here are dense feature lists in a steady 1.5.x line, and two themes recur in every one: more source collections wired in, and more of the classification pipeline made parallel or chunked. Version 1.5.3 added pysits, a Python API onto the same engine.
mice vs sits: editorial side-by-side
mice
0.0INFRA · APIS
mice can finally predict, not just estimate, from multiply imputed data.
◆ Current state
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
◆ Where it's heading
Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.
◆ Prediction
predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.
sits
0.0INFRA · APIS
An R package for satellite time series just grew a Python API.
◆ Current state
sits classifies satellite image time series — building data cubes from cloud archives, training deep learning models on them, and producing land-cover maps. The releases here are dense feature lists in a steady 1.5.x line, and two themes recur in every one: more source collections wired in, and more of the classification pipeline made parallel or chunked. Version 1.5.3 added pysits, a Python API onto the same engine.
◆ Where it's heading
The package is positioning itself as the interface layer to Earth observation archives rather than as an algorithm library. Each release absorbs another provider — Planetary Computer, Digital Earth Africa and Australia, CDSE, TERRASCOPE, Open Geo Hub, PLANET — so the differentiator is coverage and the uniform cube abstraction over it. The Python API extends the same logic to the language most of that community actually works in. Alongside, the work is increasingly about scale: chunk parallelisation, multicores sampling, GPU classification, WebGL rendering.
◆ Prediction
With collections still being added release over release, expect more providers and continued performance work on the classification and regularisation paths. The open question the entries do not answer is how far pysits tracks the R API, since it appears once and is not mentioned again in later releases.
Alternatives to mice and sits
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 mice or sits.
ggalign
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
prioritizr
Conservation planning absorbs the literature's target-setting rules as code.
jSDM
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
rsofun
An ecosystem model starts tracking carbon isotopes and land-use change.
usmap
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Recent activity from mice and sits
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agositsSNIC segmentation, imputation helpers and QGIS palette export
- 8mo agositsOne-line hotfix for a CRAN compiler requirement
- 8mo agomicemice 3.19.0 ⚡
- 11mo agositsHotfix: TAE embeddings, MPC token handling, texture divide-by-zero
- 11mo agositsA Python API arrives, alongside SAR texture measures ⚡
- 1y agomicemice 3.18.0
- 1y agositsExclusion masks, multiple tiling systems and faster segment classification
- 1y agomicemice 3.17.0
- 1y agositsFour more archives wired in, including Digital Earth Africa
- 3y agomicemice 3.16.0
- 3y agomicemice 3.15.0
- 4y agomicemice 3.14.0
Frequently asked questions
What is the difference between mice and sits?
Both compete on the same themes — r-package — within Infra & APIs. mice and sits are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is mice better than sits?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mice and sits are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to mice?
Top mice alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mice alternatives" section above for the current picks, or visit /alternatives/mice for the full list with editorial commentary on each.
What are the best alternatives to sits?
Top sits alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "sits alternatives" section above for the current picks, or visit /alternatives/sits for the full list with editorial commentary on each.