easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
Comparison · Analytics
dtplyr vs pins
A side-by-side editorial comparison of dtplyr and pins — release velocity, themes, recent moves, and the top alternatives to consider.
dtplyr vs pins: at a glance
What is dtplyr?
dtplyr stopped hijacking data.table objects and became an opt-in translator
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
What is pins?
pins keeps adding a storage backend per release while retiring its original API
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
dtplyr vs pins: editorial side-by-side
dtplyr
0.0ANALYTICS
dtplyr stopped hijacking data.table objects and became an opt-in translator
◆ Current state
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
◆ Where it's heading
The package is trailing dplyr's own feature releases rather than leading them, adding each new verb once it settles upstream. Performance work is targeted at specific verbs where data.table has a faster primitive: setorder() for arrange(), reference drops for select(), rleid() for consecutive_id(). Release cadence has thinned considerably since 2023.
◆ Prediction
Expect further one-for-one translations as dplyr adds verbs, and continued fixes around .by and non-standard column names; the entries show no sign of a broader redesign.
pins
0.0ANALYTICS
pins keeps adding a storage backend per release while retiring its original API
◆ Current state
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
◆ Where it's heading
Two long-running processes, neither dramatic. Backend coverage expands toward wherever teams already store artifacts, which increasingly means Databricks and cloud object storage rather than a shared drive. Meanwhile the legacy pin() API from before the board model has been in a staged deprecation across at least three releases, escalated each time rather than removed.
◆ Prediction
Expect another board or two as storage platforms are requested, and the legacy pin() functions to finally become errors; the format list will keep tracking whichever serializer the R community settles on.
Alternatives to dtplyr and pins
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 dtplyr or pins.
discrim
discrim settled into a thin engine shim after handing its model definitions to parsnip.
dbparser
dbparser shed its database and CSV writers to become just a DrugBank parser.
desirability2
desirability2 is making multi-metric model selection a first-class tidymodels step.
crosstalk
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
Recent activity from dtplyr and pins
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agopinsqs2 replaces qs; pins can be written in multiple formats
- 11mo agodtplyrreframe(), case_match() and consecutive_id() gain translations
- 1y agopinsPin previews on Connect; Databricks host normalization
- 1y agopinsAdds board_databricks() and switches parquet to nanoparquet
- 2y agopinspin_write() arguments must be named; Connect caches removed
- 2y agopinsMessage clarity and Google Drive dribble handling
- 2y agopinsboard_gdrive() added; cache location configurable
- 3y agodtplyrcrayon dependency dropped
- 3y agodtplyrVerbs stop auto-dispatching; lazy_dt() now required ⚡
- 3y agodtplyrdtplyr 1.2.2
- 4y agodtplyrdtplyr 1.2.1
- 4y agodtplyrEight tidyr verbs gain data.table translations
Frequently asked questions
What is the difference between dtplyr and pins?
They serve adjacent needs but don't currently overlap on shipped themes. dtplyr and pins 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 dtplyr better than pins?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dtplyr and pins 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 dtplyr?
Top dtplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dtplyr alternatives" section above for the current picks, or visit /alternatives/dtplyr for the full list with editorial commentary on each.
What are the best alternatives to pins?
Top pins alternatives in Analytics are ranked by recent ship velocity. Browse the "pins alternatives" section above for the current picks, or visit /alternatives/pins-r for the full list with editorial commentary on each.