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osmdata vs tidypredict

A side-by-side editorial comparison of osmdata and tidypredict — release velocity, themes, recent moves, and the top alternatives to consider.

osmdata vs tidypredict: at a glance

Featureosmdatatidypredict
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesopenstreetmap, overpass-api, spatial-data, breaking-changestidypredict, sql-generation, gradient-boosting, in-database-scoring
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is osmdata?

osmdata keeps tightening its Overpass query surface, breaking small things to get types right.

The last two releases are the substantive ones. 0.4.0 lets `getbb()` resolve OSM relations via Wikidata ids, adds `filter_osm_user()` to Overpass query objects, and corrects metadata typing so timestamps are POSIXct rather than locale-dependent strings. 0.3.0 dropped the re-exported magrittr pipe, raised the R floor to 4.1 for the base pipe, and fixed polygon output to follow the OGC simple-features model instead of treating every ring as an independent polygon. Earlier entries are CRAN repairs and query-construction fixes.

Read the full osmdata trajectory →

What is tidypredict?

tidypredict now translates the gradient-boosting libraries people actually deploy

tidypredict converts fitted R models into SQL and dplyr expressions so predictions can run inside a database instead of in R. The 1.1.0 release added rpart, CatBoost, and LightGBM, with full objective and tree-type coverage for the boosted models. That followed 1.0.0, which broke random-forest output into a single formula, added glmnet, and cut fit-translation time for xgboost, partykit, and ranger.

Read the full tidypredict trajectory →

osmdata vs tidypredict: editorial side-by-side

O
osmdata
ANALYTICS
0.0

osmdata keeps tightening its Overpass query surface, breaking small things to get types right.

◆ Current state

The last two releases are the substantive ones. 0.4.0 lets `getbb()` resolve OSM relations via Wikidata ids, adds `filter_osm_user()` to Overpass query objects, and corrects metadata typing so timestamps are POSIXct rather than locale-dependent strings. 0.3.0 dropped the re-exported magrittr pipe, raised the R floor to 4.1 for the base pipe, and fixed polygon output to follow the OGC simple-features model instead of treating every ring as an independent polygon. Earlier entries are CRAN repairs and query-construction fixes.

◆ Where it's heading

The pattern is deliberate correctness work: each release accepts a small breaking change to make returned objects match the standard they claim to follow, whether that is OGC polygon structure, POSIXct timestamps, or UTF-8 metadata columns. Alongside it, the Overpass query builder keeps gaining filters — by area, by out type, by osm_types, now by user and via Wikidata. The package is maturing rather than expanding.

◆ Prediction

More Overpass filter and query-object composition helpers are the likeliest next additions, since that is where both recent releases put their new surface.

T
tidypredict
ANALYTICS
0.0

tidypredict now translates the gradient-boosting libraries people actually deploy

◆ Current state

tidypredict converts fitted R models into SQL and dplyr expressions so predictions can run inside a database instead of in R. The 1.1.0 release added rpart, CatBoost, and LightGBM, with full objective and tree-type coverage for the boosted models. That followed 1.0.0, which broke random-forest output into a single formula, added glmnet, and cut fit-translation time for xgboost, partykit, and ranger.

◆ Where it's heading

The package's value scales directly with how many model types it can translate, and the recent work has concentrated on the tree ensembles that dominate tabular modelling in practice. Coverage now extends past what parsnip wraps, since raw CatBoost models are supported alongside parsnip and bonsai ones with an explicit escape hatch for categorical features. Performance work on the translation step suggests the models being converted have grown large enough for that to matter.

◆ Prediction

With the major boosting libraries covered, the remaining gap is what happens to preprocessing, so tighter integration with recipes or orbital for translating whole workflows is the natural next step.

Alternatives to osmdata and tidypredict

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 osmdata or tidypredict.

See all osmdata alternatives → · See all tidypredict alternatives →

Recent activity from osmdata and tidypredict

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoosmdataosmdata 0.4.0
  2. 5mo agotidypredicttidypredict 1.1.0 adds CatBoost, LightGBM, and rpart support
  3. 8mo agotidypredicttidypredict 1.0.1 fixes base_score extraction for xgboost 3
  4. 8mo agotidypredicttidypredict 1.0.0 unifies random forest output and adds glmnet
  5. 11mo agoosmdataosmdata 0.3.0
  6. 1y agotidypredicttidypredict 0.5.1 exports internals for the orbital package
  7. 2y agoosmdataosmdata 0.2.5 resubmitted after CRAN removal
  8. 3y agoosmdataosmdata 0.2.3 fixes test broken by sp deprecation
  9. 3y agoosmdataosmdata 0.2.2 adds out:csv queries and centre coordinates
  10. 3y agoosmdataosmdata 0.2.1 deprecates nodes_only, fixes memory leaks
  11. 3y agotidypredicttidypredict 0.5 hands maintenance to a new maintainer
  12. 4y agotidypredicttidypredict 0.4.9 relicenses to MIT and fixes SQL generation

Frequently asked questions

What is the difference between osmdata and tidypredict?

They serve adjacent needs but don't currently overlap on shipped themes. osmdata and tidypredict 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 osmdata better than tidypredict?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. osmdata and tidypredict 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 osmdata?

Top osmdata alternatives in Analytics are ranked by recent ship velocity. Browse the "osmdata alternatives" section above for the current picks, or visit /alternatives/osmdata for the full list with editorial commentary on each.

What are the best alternatives to tidypredict?

Top tidypredict alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypredict alternatives" section above for the current picks, or visit /alternatives/tidypredict for the full list with editorial commentary on each.