tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
cloudml vs sparsevctrs
A side-by-side editorial comparison of cloudml and sparsevctrs — release velocity, themes, recent moves, and the top alternatives to consider.
cloudml vs sparsevctrs: 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 sparsevctrs?
Sparse vectors stopped being a storage trick and became something you can do arithmetic on
sparsevctrs supplies sparse vectors that live inside ordinary data frames and tibbles, which is what lets tidymodels carry wide, mostly-zero feature matrices without densifying them. Through 0.2.0 and 0.3.0 the package built out a computation layer on top of that storage — first summary statistics, then scalar and element-wise arithmetic — and everything since has been correctness work at the C level.
cloudml vs sparsevctrs: 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.
sparsevctrs
0.0ANALYTICS
Sparse vectors stopped being a storage trick and became something you can do arithmetic on
◆ Current state
sparsevctrs supplies sparse vectors that live inside ordinary data frames and tibbles, which is what lets tidymodels carry wide, mostly-zero feature matrices without densifying them. Through 0.2.0 and 0.3.0 the package built out a computation layer on top of that storage — first summary statistics, then scalar and element-wise arithmetic — and everything since has been correctness work at the C level.
◆ Where it's heading
The release pattern splits cleanly at 0.3.0. Before it, new functions arrive in batches; after it, five consecutive releases are bug fixes, and the bugs are the kind that come with hand-written sparse kernels: a stack imbalance when sparse_multiplication() returns all zeros, undefined behaviour in multiplication, type errors in sparse_is_na(), coercion failures on NA input. That is the expected cost of an ALTREP-backed numerical layer, and the fixes are landing steadily.
◆ Prediction
With the arithmetic surface in place and the recent releases all narrow fixes, the next one is more likely another correctness patch than a new function family. The R devel fix in 0.3.5 suggests upcoming R releases are the current source of breakage.
Alternatives to cloudml and sparsevctrs
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 sparsevctrs.
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 sparsevctrs alternatives →
Recent activity from cloudml and sparsevctrs
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agosparsevctrsSparse character vector fix for R devel
- 0y agocloudmlDocumentation updated for CRAN
- 1y agosparsevctrsStack imbalance in sparse multiplication fixed
- 1y agosparsevctrsSparse matrix coercion no longer errors on NA input
- 1y agosparsevctrssparsity() fixed for classed numeric vectors
- 1y agosparsevctrsUndefined behaviour in sparse multiplication fixed
- 1y agosparsevctrsScalar and element-wise arithmetic for sparse vectors ⚡
- 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 sparsevctrs?
They serve adjacent needs but don't currently overlap on shipped themes. cloudml and sparsevctrs 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 cloudml better than sparsevctrs?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cloudml and sparsevctrs 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 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 sparsevctrs?
Top sparsevctrs alternatives in Analytics are ranked by recent ship velocity. Browse the "sparsevctrs alternatives" section above for the current picks, or visit /alternatives/sparsevctrs for the full list with editorial commentary on each.