tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of hoardr and sparsevctrs — release velocity, themes, recent moves, and the top alternatives to consider.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.
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.
hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.
This is infrastructure that has reached its final shape. Three of the last three releases were reactive: two responses to CRAN test-failure notifications, one to a maintainer handover. The single behavioural change in that stretch — forward slashes in paths on every operating system — is a consistency fix for downstream packages rather than a feature. Its release cadence is set by CRAN's checks, not by demand.
Expect the next release to be triggered by another CRAN check failure rather than by new functionality, matching every release since 2018.
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.
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.
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.
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 hoardr or sparsevctrs.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all hoardr alternatives → · See all sparsevctrs alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. hoardr 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hoardr 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.
Top hoardr alternatives in Analytics are ranked by recent ship velocity. Browse the "hoardr alternatives" section above for the current picks, or visit /alternatives/hoardr for the full list with editorial commentary on each.
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.