Tplyr
Tplyr made clinical summary tables explain where every number came from.
A side-by-side editorial comparison of orbital and tidytlg — release velocity, themes, recent moves, and the top alternatives to consider.
Turning fitted tidymodels into SQL, one model family at a time — and the boosting engines just landed.
orbital converts a fitted tidymodels workflow into a database expression so prediction runs where the data lives, no R session in the loop. Its value is entirely a function of coverage, and 0.5.0 was the largest coverage release yet: catboost and lightgbm boosted trees, rpart decision trees, earth-backed MARS, glmnet multinomial regression, and both randomForest and ranger random forests, all for numeric, class, and probability predictions. The 0.5.1 follow-up is corrective, fixing SQL that Snowflake and other engines rejected because it cast booleans directly to numeric.
A tables-listings-graphs package that reached CRAN and then went quiet.
tidytlg generates clinical tables, listings, and graphs from tidyverse-style pipelines, maintained under the pharmaverse organisation. All four releases in the window are from a single eight-month stretch in 2023, and their content is CRAN preparation, a logging-dependency swap, and multi-file support. Release notes are merge lists rather than described changes.
orbital converts a fitted tidymodels workflow into a database expression so prediction runs where the data lives, no R session in the loop. Its value is entirely a function of coverage, and 0.5.0 was the largest coverage release yet: catboost and lightgbm boosted trees, rpart decision trees, earth-backed MARS, glmnet multinomial regression, and both randomForest and ranger random forests, all for numeric, class, and probability predictions. The 0.5.1 follow-up is corrective, fixing SQL that Snowflake and other engines rejected because it cast booleans directly to numeric.
The package has been working outward in rings: recipe preprocessing steps first, then model types, then post-processing via the tailor package in 0.4.0, with show_query() added so users can inspect what actually gets sent. Recent releases show the constraint shifting from R-side translation to SQL dialect compatibility — the bugs now are about what a specific database will accept, not whether a model can be expressed. estimate_orbital_size() in 0.5.1 acknowledges the other practical limit, since generated expressions can grow large enough to matter before you generate them.
With the major boosting and ensemble engines covered, expect the next releases to keep chasing dialect-specific SQL correctness across warehouses rather than adding model families.
tidytlg generates clinical tables, listings, and graphs from tidyverse-style pipelines, maintained under the pharmaverse organisation. All four releases in the window are from a single eight-month stretch in 2023, and their content is CRAN preparation, a logging-dependency swap, and multi-file support. Release notes are merge lists rather than described changes.
The visible arc is getting onto CRAN and staying installable — vignette corrections per CRAN comments, a badge, a check fix, and replacing the timber logging package with logrx. The one functional addition is multiple-file support. There has been no release since October 2023, so on this evidence the package is stable or dormant rather than actively developing.
The entries give no signal about planned work; with nothing shipped in roughly two years, the more likely next event is a maintenance release triggered by a dependency or CRAN check than a feature.
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 orbital or tidytlg.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
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 orbital alternatives → · See all tidytlg alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. orbital and tidytlg 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. orbital and tidytlg 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 orbital alternatives in Analytics are ranked by recent ship velocity. Browse the "orbital alternatives" section above for the current picks, or visit /alternatives/orbital for the full list with editorial commentary on each.
Top tidytlg alternatives in Analytics are ranked by recent ship velocity. Browse the "tidytlg alternatives" section above for the current picks, or visit /alternatives/tidytlg for the full list with editorial commentary on each.