pins
pins keeps adding a storage backend per release while retiring its original API
Comparison · Analytics
bigrquery vs themis
A side-by-side editorial comparison of bigrquery and themis — release velocity, themes, recent moves, and the top alternatives to consider.
bigrquery vs themis: at a glance
What is bigrquery?
bigrquery went MIT, then handed its slowest path to the BigQuery Storage API
bigrquery is the R client for Google BigQuery. Version 1.5.0 was the structural release - MIT relicensing, removal of the long-deprecated non-bq_ API, and a move to the second edition of the dbplyr interface with a much fuller DBI implementation. Since then the work has been about the two things that hurt in practice: download throughput and cost visibility.
What is themis?
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
bigrquery vs themis: editorial side-by-side
bigrquery
0.0ANALYTICS
bigrquery went MIT, then handed its slowest path to the BigQuery Storage API
◆ Current state
bigrquery is the R client for Google BigQuery. Version 1.5.0 was the structural release - MIT relicensing, removal of the long-deprecated non-bq_ API, and a move to the second edition of the dbplyr interface with a much fuller DBI implementation. Since then the work has been about the two things that hurt in practice: download throughput and cost visibility.
◆ Where it's heading
The package is settling into being a well-behaved DBI and dbplyr backend rather than a bespoke API wrapper, and offloading its hard parts to specialist packages - clock for date parsing, bigrquerystorage for bulk downloads, gargle for auth. The recent additions read like responses to production use: job labels for cost allocation, microsecond timestamp precision, a configurable quiet option.
◆ Prediction
Expect bigrquerystorage to move from optional to expected for large reads, and further work on upload fidelity, where digits and timezone handling have needed repeated correction.
themis
2.5ANALYTICS
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
◆ Current state
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
◆ Where it's heading
The package grows by adding algorithms rather than restructuring itself. tomek() was rewritten to handle multiple classes and drop the unbalanced dependency, case weights arrived at 1.0.0, and cluster-centroid and condensed-nearest-neighbour under-sampling arrive now — each shipped as both a recipes step and a direct-implementation function.
◆ Prediction
Expect further under- and over-sampling methods in the same paired form, as the package fills out coverage of the standard class-imbalance literature.
Alternatives to bigrquery and themis
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 bigrquery or themis.
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 bigrquery alternatives → · See all themis alternatives →
Recent activity from bigrquery and themis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10d agothemisthemis 1.1.0 adds cluster-centroid and CNN under-sampling
- 3mo agobigrqueryJob labels for cost allocation; microsecond upload precision
- 11mo agobigrqueryUses bigrquerystorage automatically for large downloads
- 11mo agobigrqueryDevelopment snapshot advancing 1.4.0 deprecations
- 1y agothemisthemis 1.0.3 corrects resampling direction in documentation
- 2y agobigrqueryForward compatibility with an upcoming dbplyr release
- 2y agobigrqueryMIT relicensing, dbplyr second edition, full DBI support ⚡
- 2y agothemisthemis 1.0.2 makes internal consistency and speed changes
- 3y agobigrquerySyncs with gargle's OAuth client rename
- 3y agothemisthemis 1.0.1 fixes upsampling errors when none is needed
- 4y agothemisthemis 1.0.0 adds case weights to up- and down-sampling
- 4y agothemisthemis 0.2.2 rewrites tomek() for multiclass, drops a dependency
Frequently asked questions
What is the difference between bigrquery and themis?
They serve adjacent needs but don't currently overlap on shipped themes. themis is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is bigrquery better than themis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. themis is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to bigrquery?
Top bigrquery alternatives in Analytics are ranked by recent ship velocity. Browse the "bigrquery alternatives" section above for the current picks, or visit /alternatives/bigrquery for the full list with editorial commentary on each.
What are the best alternatives to themis?
Top themis alternatives in Analytics are ranked by recent ship velocity. Browse the "themis alternatives" section above for the current picks, or visit /alternatives/themis for the full list with editorial commentary on each.