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Comparison · Analytics
collapse vs seriation
A side-by-side editorial comparison of collapse and seriation — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
collapse vs seriation: at a glance
What is collapse?
collapse got a JSS paper and a 7x fmean speedup in the same release.
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
What is seriation?
seriation stopped shipping algorithms and started shipping a way to pick between them.
seriation finds meaningful orderings for matrices, distance objects and dendrograms, and carries a large registry of methods from classic combinatorial criteria to t-SNE and UMAP embeddings. The 1.5.0 release added a layer above that registry — seriate_best(), seriate_rep() and seriate_improve() — which run randomized methods repeatedly, in parallel, and keep the best result. Recent work is definitional and numeric rather than additive: 1.5.8 corrects the linear seriation criterion to match Hubert and Schultz's original 1976 definition.
collapse vs seriation: editorial side-by-side
collapse
0.0ANALYTICS
collapse got a JSS paper and a 7x fmean speedup in the same release.
◆ Current state
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
◆ Where it's heading
The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.
◆ Prediction
Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.
seriation
0.0ANALYTICS
seriation stopped shipping algorithms and started shipping a way to pick between them.
◆ Current state
seriation finds meaningful orderings for matrices, distance objects and dendrograms, and carries a large registry of methods from classic combinatorial criteria to t-SNE and UMAP embeddings. The 1.5.0 release added a layer above that registry — seriate_best(), seriate_rep() and seriate_improve() — which run randomized methods repeatedly, in parallel, and keep the best result. Recent work is definitional and numeric rather than additive: 1.5.8 corrects the linear seriation criterion to match Hubert and Schultz's original 1976 definition.
◆ Where it's heading
The package has shifted from breadth to judgment. Through 1.3.x the additions were new methods; from 1.5.0 the registry started carrying metadata about the methods — whether they are randomized, what criterion they optimize — so the package could choose and evaluate on the user's behalf. The 1.5.6 replacement of FORTRAN with C for BEA and ME points the same way, reducing the legacy surface underneath that machinery.
◆ Prediction
Further criterion audits are the likeliest next move, since 1.5.8 shows a published definition being reconciled against the implementation and the registry now records what each method optimizes. Expect corrections rather than new seriation algorithms.
Alternatives to collapse and seriation
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 collapse or seriation.
geodist
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors
errors keeps making uncertainty print the way each scientific field expects.
CMAQ
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls
enpls has not changed its statistics since 2016 — only its website, twice.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
See all collapse alternatives → · See all seriation alternatives →
Recent activity from collapse and seriation
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
- 7mo agocollapseNegative zero now hashes equal to zero across the package
- 8mo agocollapsecollap() no longer double-aggregates external weights
- 9mo agocollapseCustom unlist() preserves attributes
- 0y agoseriationseriation 1.5.8 realigns linear criterion with Hubert and Schultz
- 0y agocollapseAssorted bug fixes
- 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
- 1y agoseriationseriation 1.5.7 adds BK_unconstrained, handles tiny inputs
- 1y agoseriationseriation 1.5.6 replaces FORTRAN BEA with C, modernizes allocation
- 2y agoseriationseriation 1.5.5 digest: AOE method, rep parameter, MDS_angle fix
- 3y agoseriationseriation 1.5.1 refines pimage, permute and hmap
- 3y agoseriationseriation 1.5.0 adds seriate_best and parallel repeated search ⚡
Frequently asked questions
What is the difference between collapse and seriation?
Both compete on the same themes — r-package — within Analytics. collapse and seriation 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 collapse better than seriation?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collapse and seriation 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 Analytics products to evaluate alongside.
What are the best alternatives to collapse?
Top collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.
What are the best alternatives to seriation?
Top seriation alternatives in Analytics are ranked by recent ship velocity. Browse the "seriation alternatives" section above for the current picks, or visit /alternatives/seriation-r for the full list with editorial commentary on each.