pins
pins keeps adding a storage backend per release while retiring its original API
Comparison · Analytics
dtplyr vs sparklyr
A side-by-side editorial comparison of dtplyr and sparklyr — release velocity, themes, recent moves, and the top alternatives to consider.
dtplyr vs sparklyr: 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 sparklyr?
sparklyr now spends its releases absorbing dbplyr changes and feeding pysparklyr
sparklyr connects R to Spark, and almost nothing in this window originates inside the package. Releases restore compatibility after dbplyr changes its SQL generation, adapt to Spark 4.0 and to R 4.4's version-comparison changes, and convert functions into S3 methods so pysparklyr can supply its own implementations.
dtplyr vs sparklyr: 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.
sparklyr
0.0ANALYTICS
sparklyr now spends its releases absorbing dbplyr changes and feeding pysparklyr
◆ Current state
sparklyr connects R to Spark, and almost nothing in this window originates inside the package. Releases restore compatibility after dbplyr changes its SQL generation, adapt to Spark 4.0 and to R 4.4's version-comparison changes, and convert functions into S3 methods so pysparklyr can supply its own implementations.
◆ Where it's heading
Two dependencies set the agenda. dbplyr repeatedly changes identifier quoting and lazy-table internals, and each change costs sparklyr a release. Meanwhile the package is being hollowed into a backend: ml_fit(), spark_apply(), spark_write_delta() and now tune_grid_spark() exist as methods so that pysparklyr, the Databricks Connect path, can override them. Dependency removal - tibble, rappdirs, digest - runs alongside as the package slims down.
◆ Prediction
Expect the next releases to continue tracking dbplyr and Spark versions, and more functions to be converted to methods as functionality shifts toward pysparklyr; new capability arriving in sparklyr itself looks unlikely.
Alternatives to dtplyr and sparklyr
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 sparklyr.
tsibble
tsibble shipped one release in five and a half years - the data structure is finished
yardstick
yardstick made fairness metrics a first-class part of tidymodels evaluation
tune
tune extends tuning past the model itself to postprocessors, and adds a second parallel backend
leaflet
leaflet relicensed to MIT and finished migrating off R's retired spatial stack
ggpubr
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
See all dtplyr alternatives → · See all sparklyr alternatives →
Recent activity from dtplyr and sparklyr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agosparklyrRestores compatibility after dbplyr changed Hive quoting
- 3mo agosparklyrAdds tune_grid_spark() for pysparklyr to implement
- 10mo agosparklyrFixes lazy-table field lookup and a name collision
- 11mo agodtplyrreframe(), case_match() and consecutive_id() gain translations
- 1y agosparklyrCatches up with released Spark 4.0; ml_load() reads via Spark
- 2y agosparklyrDatabricks autoloader streaming ingestion; R 4.4 fixes
- 2y agosparklyrDrops tibble and rappdirs; retires Spark 2.3 JARs
- 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 sparklyr?
They serve adjacent needs but don't currently overlap on shipped themes. dtplyr and sparklyr 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 sparklyr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dtplyr and sparklyr 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 sparklyr?
Top sparklyr alternatives in Analytics are ranked by recent ship velocity. Browse the "sparklyr alternatives" section above for the current picks, or visit /alternatives/sparklyr for the full list with editorial commentary on each.