rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
embed vs rgbif
A side-by-side editorial comparison of embed and rgbif — release velocity, themes, recent moves, and the top alternatives to consider.
embed vs rgbif: at a glance
What is embed?
embed keeps adding encoding steps while shedding its deep-learning dependencies
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
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()`.
embed vs rgbif: editorial side-by-side
embed
0.0ANALYTICS
embed keeps adding encoding steps while shedding its deep-learning dependencies
◆ Current state
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
◆ Where it's heading
Two quiet directions run through these releases. One is making the steps tunable rather than fixed, so they participate properly in tidymodels grids. The other is boundary maintenance: heavy dependencies pushed to Suggests, overlapping steps handed to the package that owns them. Recent releases are thin and fix-driven.
◆ Prediction
Expect further consolidation with textrecipes over which package owns which encoding step, and continued upkeep against xgboost and uwot releases rather than new step families.
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 embed 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 embed 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.
Recent activity from embed and rgbif
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agorgbifrgbif 3.8.5 adds occurrence download statistics functions
- 6mo agoembedstep_umap() zero-component bug fixed
- 8mo agoembedCompatibility with all xgboost versions
- 8mo agorgbifrgbif 3.8.4 moves name matching to GBIF API v2
- 11mo agoembedstep_lencode() adds analytical likelihood encoding with pooling
- 11mo agorgbifrgbif 3.8.3 adds GRSciColl search, relays GBIF paging throttle
- 1y agorgbifrgbif 3.8.2 resolves download DOIs to keys
- 1y agoembedUMAP initial and target_weight become tunable
- 1y agorgbifrgbif 3.8.1 adds SQL-based occurrence downloads ⚡
- 2y agorgbifrgbif 3.8.0 soft-deprecates occ_data(), adds download describe
- 2y agoembedkeras and tensorflow moved to Suggests
- 2y agoembedstep_collapse_stringdist() returns factors
Frequently asked questions
What is the difference between embed and rgbif?
They serve adjacent needs but don't currently overlap on shipped themes. embed 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 embed better than rgbif?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. embed 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 embed?
Top embed alternatives in Analytics are ranked by recent ship velocity. Browse the "embed alternatives" section above for the current picks, or visit /alternatives/embed 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.