tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
crul vs orbital
A side-by-side editorial comparison of crul and orbital — release velocity, themes, recent moves, and the top alternatives to consider.
crul vs orbital: at a glance
What is crul?
crul took mocking back from webmockr and made it a property of the client itself
crul is the R6-based HTTP client underneath much of rOpenSci's package stack, covering synchronous requests, three flavours of async, pagination and retries. Its 1.6.0 release in July 2025 changed where test mocking lives: each client — HttpClient, Async, AsyncVaried — now takes a mocking parameter at initialisation or per method, and the standalone mock() function is deprecated. Mocking used to be something webmockr switched on from outside; it is now a setting on the client.
What is orbital?
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.
crul vs orbital: editorial side-by-side
crul
0.0ANALYTICS
crul took mocking back from webmockr and made it a property of the client itself
◆ Current state
crul is the R6-based HTTP client underneath much of rOpenSci's package stack, covering synchronous requests, three flavours of async, pagination and retries. Its 1.6.0 release in July 2025 changed where test mocking lives: each client — HttpClient, Async, AsyncVaried — now takes a mocking parameter at initialisation or per method, and the standalone mock() function is deprecated. Mocking used to be something webmockr switched on from outside; it is now a setting on the client.
◆ Where it's heading
The async surface has been the growth area for years — retries reached Async, AsyncVaried, AsyncQueue and HttpRequest in 1.4, AsyncQueue gained the response accessors in 1.2, and 1.5.0 wired async requests up to webmockr. The 1.6.0 change reverses that direction of dependency, and it landed within a minute of webmockr's own release severing its tie to vcr. Read together, the rOpenSci HTTP stack is being deliberately untangled so each package can be used without the others.
◆ Prediction
With mock() deprecated rather than removed, the next major release is the likely point of deletion. Expect the remaining work to follow the same decoupling theme rather than adding request features.
orbital
0.0ANALYTICS
Turning fitted tidymodels into SQL, one model family at a time — and the boosting engines just landed.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to crul and orbital
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 crul or orbital.
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 crul alternatives → · See all orbital alternatives →
Recent activity from crul and orbital
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoorbitalSnowflake-compatible SQL for dummy and NA steps
- 5mo agoorbitalcatboost, lightgbm, ranger and four more model families translate to SQL ⚡
- 8mo agoorbitalCompatibility with new xgboost versions
- 8mo agoorbitalPost-processing adjustments from tailor become translatable
- 11mo agoorbitalPCA step translation bugs cleared
- 1y agocrulMocking becomes a client parameter, independent of webmockr ⚡
- 1y agoorbitalClass and probability predictions arrive, with glm and xgboost
- 2y agocrulAsync requests become mockable through webmockr
- 2y agocrulDocumentation fixes and test helper tweak
- 3y agocrulHTTP retries reach the async classes
- 3y agocrulClearer error for mismatched urls and disk lengths
- 4y agocrulAsyncQueue gains response accessors; results print as a summary
Frequently asked questions
What is the difference between crul and orbital?
They serve adjacent needs but don't currently overlap on shipped themes. crul and orbital 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 crul better than orbital?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. crul and orbital 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 crul?
Top crul alternatives in Analytics are ranked by recent ship velocity. Browse the "crul alternatives" section above for the current picks, or visit /alternatives/crul for the full list with editorial commentary on each.
What are the best alternatives to orbital?
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.