rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
mlr3learners vs rgbif
A side-by-side editorial comparison of mlr3learners and rgbif — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3learners vs rgbif: at a glance
What is mlr3learners?
mlr3learners spends its releases absorbing upstream churn
mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.
What is rgbif?
rgbif is steadily pushing users off paged searching and onto real downloads.
rgbif ships several times a year and the recent releases cluster around downloads. 3.8.1 added `occ_download_sql()` for SQL-based occurrence downloads; 3.8.2 added DOI-to-download-key resolution and institutionKey downloads; 3.8.3 relayed GBIF's new throttling of bulk paging through `occ_search()` with a message pointing users at `occ_download()`; 3.8.5 added a family of `occ_download_stats_*()` functions plus multiple-taxonomy and verbatim-extension downloads. Alongside that, `name_backbone()` moved to GBIF API v2, and 3.8.0 soft-deprecated `occ_data()`.
mlr3learners vs rgbif: editorial side-by-side
mlr3learners
0.0ANALYTICS
mlr3learners spends its releases absorbing upstream churn
◆ Current state
mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.
◆ Where it's heading
The package's job is insulation, and the changelog shows what that costs — compatibility-only releases interleaved with small capability additions that expose more of each upstream model. The direction of travel is toward giving users access to the raw upstream objects rather than hiding them.
◆ Prediction
Expect the next release to track another upstream version bump, with incremental exposure of learner-specific fields continuing alongside.
rgbif
0.0ANALYTICS
rgbif is steadily pushing users off paged searching and onto real downloads.
◆ Current state
rgbif ships several times a year and the recent releases cluster around downloads. 3.8.1 added `occ_download_sql()` for SQL-based occurrence downloads; 3.8.2 added DOI-to-download-key resolution and institutionKey downloads; 3.8.3 relayed GBIF's new throttling of bulk paging through `occ_search()` with a message pointing users at `occ_download()`; 3.8.5 added a family of `occ_download_stats_*()` functions plus multiple-taxonomy and verbatim-extension downloads. Alongside that, `name_backbone()` moved to GBIF API v2, and 3.8.0 soft-deprecated `occ_data()`.
◆ Where it's heading
Two things are happening at once. GBIF is discouraging bulk retrieval through the search API, and rgbif is building out the download path fast enough to absorb the traffic — SQL queries, DOI round-tripping, format description, and now statistics about the downloads themselves. Metadata coverage has expanded in parallel, with a dozen `dataset_*()` functions in 3.7.9 and GRSciColl institution search in 3.8.3. The deprecations are consistent: `occ_data()`, `occ_facet()`, `occ_count(type=)` all retired in favour of narrower replacements.
◆ Prediction
The download surface is where the next additions will land — likely more SQL-download tooling and further statistics endpoints, following 3.8.1 and 3.8.5.
Alternatives to mlr3learners and rgbif
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 mlr3learners or rgbif.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
taxize
taxize spends its releases absorbing other people's API changes, one dead source at a time.
See all mlr3learners alternatives → · See all rgbif alternatives →
Recent activity from mlr3learners and rgbif
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3learnerspredict_raw across all learners, plus probit and ranger internals
- 4mo agorgbifrgbif 3.8.5 adds occurrence download statistics functions
- 8mo agomlr3learnersxgboost 3.1.2.1 compatibility
- 8mo agorgbifrgbif 3.8.4 moves name matching to GBIF API v2
- 9mo agomlr3learnersUncertainty estimation methods for ranger regression
- 10mo agomlr3learnersDevelopment snapshot: LDA test adjustment
- 11mo agorgbifrgbif 3.8.3 adds GRSciColl search, relays GBIF paging throttle
- 1y agorgbifrgbif 3.8.2 resolves download DOIs to keys
- 1y agomlr3learnerskknn learners restored after returning to CRAN
- 1y agomlr3learnerskknn learners removed after CRAN archival
- 1y agorgbifrgbif 3.8.1 adds SQL-based occurrence downloads ⚡
- 2y agorgbifrgbif 3.8.0 soft-deprecates occ_data(), adds download describe
Frequently asked questions
What is the difference between mlr3learners and rgbif?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3learners and rgbif 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 mlr3learners better than rgbif?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3learners and rgbif 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 mlr3learners?
Top mlr3learners alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3learners alternatives" section above for the current picks, or visit /alternatives/mlr3learners for the full list with editorial commentary on each.
What are the best alternatives to rgbif?
Top rgbif alternatives in Analytics are ranked by recent ship velocity. Browse the "rgbif alternatives" section above for the current picks, or visit /alternatives/rgbif for the full list with editorial commentary on each.