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Comparison · Analytics
bundle vs rstantools
A side-by-side editorial comparison of bundle and rstantools — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:compatibility
bundle vs rstantools: at a glance
What is bundle?
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
What is rstantools?
The scaffolding layer for Stan-backed R packages, maintained rather than extended.
rstantools generates and maintains the build infrastructure that lets an R package ship Stan models — the inst/stan layout, the auto-generated C++, the Rcpp module loading, and the posterior_* generics downstream packages implement. Its releases are dominated by keeping that scaffolding compiling as Stan, StanHeaders, and rstan move underneath it. Version 2.7.0 continues that pattern, its one user-facing change being an allowance for deprecated syntax in specified versions of specified packages.
bundle vs rstantools: editorial side-by-side
bundle
0.0ANALYTICS
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
◆ Current state
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
◆ Where it's heading
Coverage is the product, so the release cadence is set by the ecosystem rather than by a roadmap. dbarts arrived in 0.1.2, along with extra work to preserve xgboost's nfeatures and feature_names through a round trip; 0.1.3 exists because xgboost changed its model format again. The 0.1.1 fix — recipes steps nested inside workflows — points at the same underlying issue one level up, where the object needing bundling is buried inside a tidymodels pipeline rather than passed directly.
◆ Prediction
Expect the next release to follow the same trigger: either a new parsnip engine that carries external pointers, or another upstream format change in one of the engines already covered. xgboost has now forced two of the four releases.
rstantools
2.5ANALYTICS
The scaffolding layer for Stan-backed R packages, maintained rather than extended.
◆ Current state
rstantools generates and maintains the build infrastructure that lets an R package ship Stan models — the inst/stan layout, the auto-generated C++, the Rcpp module loading, and the posterior_* generics downstream packages implement. Its releases are dominated by keeping that scaffolding compiling as Stan, StanHeaders, and rstan move underneath it. Version 2.7.0 continues that pattern, its one user-facing change being an allowance for deprecated syntax in specified versions of specified packages.
◆ Where it's heading
This is a stable dependency in maintenance mode, and the release history reads accordingly: compatibility shims for new rstan and Stan RNG versions, C++ standard bumps, and pkgdown housekeeping. The last substantive API growth was 2.5.0's loo_epred() generic and discrete-data loo_pit(). Contributor churn is visible in recent releases, with several first-time contributors handling infrastructure rather than statistics.
◆ Prediction
Expect the next releases to continue tracking Stan and rstan breakage as it arrives; nothing in the recent entries points to new generics or a change in the package-generation model.
Alternatives to bundle and rstantools
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 bundle or rstantools.
DoseFinding
New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing
webmockr
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
crul
crul took mocking back from webmockr and made it a property of the client itself
dendroNetwork
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
chattr
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
See all bundle alternatives → · See all rstantools alternatives →
Recent activity from bundle and rstantools
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 19d agorstantoolsDeprecated syntax allowed for pinned package versions
- 7mo agorstantoolspkgdown theme refresh, C++14 dropped from SystemRequirements
- 8mo agobundlexgboost bundling updated for newer model versions
- 11mo agorstantoolsloo_epred() generic added, loo_pit() extended to discrete data
- 1y agobundledbarts BART models become bundleable
- 2y agorstantoolsStandalone Stan functions fixed for rstan 2.33+
- 2y agobundleRecipes steps inside workflows now bundle correctly
- 3y agorstantoolsinit_cpp deprecated, standalone-function bugfix under Stan 2.31
- 3y agorstantoolsC++17 standard adopted, standalone function export reworked
- 3y agobundleFirst CRAN release
Frequently asked questions
What is the difference between bundle and rstantools?
Both compete on the same themes — compatibility — within Analytics. rstantools 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.
Is bundle better than rstantools?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rstantools 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 Analytics products to evaluate alongside.
What are the best alternatives to bundle?
Top bundle alternatives in Analytics are ranked by recent ship velocity. Browse the "bundle alternatives" section above for the current picks, or visit /alternatives/bundle for the full list with editorial commentary on each.
What are the best alternatives to rstantools?
Top rstantools alternatives in Analytics are ranked by recent ship velocity. Browse the "rstantools alternatives" section above for the current picks, or visit /alternatives/rstantools for the full list with editorial commentary on each.