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Comparison · Analytics
broom vs sparklyr
A side-by-side editorial comparison of broom and sparklyr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:maintenance
broom vs sparklyr: at a glance
What is broom?
broom's release calendar is now set by CRAN checks, not by new tidiers.
broom converts model objects from across R's statistical ecosystem into tidy data frames. Four of its last six releases exist purely to resolve R CMD check warnings and errors on r-devel or to absorb upstream package changes. Maintainership passed to Emil Hvitfeldt at 1.0.11.
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.
broom vs sparklyr: editorial side-by-side
broom
0.0ANALYTICS
broom's release calendar is now set by CRAN checks, not by new tidiers.
◆ Current state
broom converts model objects from across R's statistical ecosystem into tidy data frames. Four of its last six releases exist purely to resolve R CMD check warnings and errors on r-devel or to absorb upstream package changes. Maintainership passed to Emil Hvitfeldt at 1.0.11.
◆ Where it's heading
Carrying hundreds of tidier methods for model classes it does not own, broom's workload is dominated by other projects' breaking changes and CRAN's evolving checks. New tidier coverage has largely migrated to the packages that define the models, leaving broom as a compatibility surface.
◆ Prediction
Expect the cadence to stay reactive, with releases triggered by r-devel check failures and upstream API shifts rather than expanded model coverage.
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 broom 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 broom or sparklyr.
bayesplot
bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.
animation
Contribution-driven maintenance on a package whose last structural change was magick support.
pins
pins keeps adding a storage backend per release while retiring its original API
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
See all broom alternatives → · See all sparklyr alternatives →
Recent activity from broom and sparklyr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agosparklyrRestores compatibility after dbplyr changed Hive quoting
- 3mo agobroombroom 1.0.13 relocates a test fixture to clear an r-devel warning
- 3mo agobroombroom 1.0.12 tracks renamed summary() output fields
- 3mo agosparklyrAdds tune_grid_spark() for pysparklyr to implement
- 8mo agobroombroom 1.0.11 transfers maintainership to Emil Hvitfeldt
- 10mo agosparklyrFixes lazy-table field lookup and a name collision
- 11mo agobroombroom 1.0.10 clears an r-devel namespacing warning
- 1y agobroombroom 1.0.9 requires R 4.1 and repairs epiR compatibility
- 1y agosparklyrCatches up with released Spark 4.0; ml_load() reads via Spark
- 1y agobroombroom 1.0.8 fixes cluster-robust intervals, drops orcutt tidiers
- 2y agosparklyrDatabricks autoloader streaming ingestion; R 4.4 fixes
- 2y agosparklyrDrops tibble and rappdirs; retires Spark 2.3 JARs
Frequently asked questions
What is the difference between broom and sparklyr?
Both compete on the same themes — maintenance — within Analytics. broom 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 broom better than sparklyr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. broom 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 broom?
Top broom alternatives in Analytics are ranked by recent ship velocity. Browse the "broom alternatives" section above for the current picks, or visit /alternatives/broom 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.