tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
cloudml vs rstantools
A side-by-side editorial comparison of cloudml and rstantools — release velocity, themes, recent moves, and the top alternatives to consider.
cloudml vs rstantools: at a glance
What is cloudml?
Six years since the last functional change, and Google renamed the service it wraps in the release before that
cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.
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.
cloudml vs rstantools: editorial side-by-side
cloudml
0.0ANALYTICS
Six years since the last functional change, and Google renamed the service it wraps in the release before that
◆ Current state
cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.
◆ Where it's heading
The visible arc is short and stops abruptly. Releases through 2018 tracked the TensorFlow runtime version and patched packaging problems; 0.6.1 added a customCommands hook so users could run OS-level setup before package installation, and adjusted to the service's new name. Then nothing for six years. A 2025 release containing only documentation changes is the standard signal of a package being kept on CRAN rather than being developed.
◆ Prediction
There is nothing in this feed to support a prediction of functional work. The most likely next event is another CRAN-driven documentation patch, or archival.
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 cloudml 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 cloudml or rstantools.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all cloudml alternatives → · See all rstantools alternatives →
Recent activity from cloudml 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
- 11mo agorstantoolsloo_epred() generic added, loo_pit() extended to discrete data
- 0y agocloudmlDocumentation updated for CRAN
- 2y agorstantoolsStandalone Stan functions fixed for rstan 2.33+
- 3y agorstantoolsinit_cpp deprecated, standalone-function bugfix under Stan 2.31
- 3y agorstantoolsC++17 standard adopted, standalone function export reworked
- 6y agocloudmlai-platform command adopted; custom pre-install commands added
- 7y agocloudmlDefault runtime moves to TensorFlow 1.9
- 8y agocloudmlPatch for CRAN results and a packrat error
- 8y agocloudmlCloud training, GPU jobs, tuning and deployment from R
Frequently asked questions
What is the difference between cloudml and rstantools?
They serve adjacent needs but don't currently overlap on shipped themes. 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 cloudml 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 cloudml?
Top cloudml alternatives in Analytics are ranked by recent ship velocity. Browse the "cloudml alternatives" section above for the current picks, or visit /alternatives/cloudml 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.