easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
A side-by-side editorial comparison of discrim and sparklyr — release velocity, themes, recent moves, and the top alternatives to consider.
discrim settled into a thin engine shim after handing its model definitions to parsnip.
discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.
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.
discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.
The package built out method coverage early, adding quadratic discriminant analysis in 0.1.2, the sda and sparsediscrim engines in 0.1.3 and case weights in 1.0.0, then stopped growing. Handing definitions upstream to parsnip in 0.2.0 confirmed the shape: discrim is where engines are wired, not where the API lives. Cadence since 2022 is roughly one small fix a year.
Nothing in the entries points to new methods or engines; the next release is most likely another CRAN or prediction-path fix.
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.
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.
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.
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 discrim or sparklyr.
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
dbparser shed its database and CSV writers to become just a DrugBank parser.
desirability2 is making multi-metric model selection a first-class tidymodels step.
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
See all discrim alternatives → · See all sparklyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. discrim 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discrim 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.
Top discrim alternatives in Analytics are ranked by recent ship velocity. Browse the "discrim alternatives" section above for the current picks, or visit /alternatives/discrim for the full list with editorial commentary on each.
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.