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bigrquery vs scales

A side-by-side editorial comparison of bigrquery and scales — release velocity, themes, recent moves, and the top alternatives to consider.

bigrquery vs scales: at a glance

Featurebigrqueryscales
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbigquery, dbi, dbplyr, licensingr, ggplot2, data-visualization, axis-labels
Last editorial update55m ago2h ago
WebsiteVisit →Visit →

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.

Read the full bigrquery trajectory →

What is scales?

scales keeps widening what ggplot2 can put on an axis.

scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.

Read the full scales trajectory →

bigrquery vs scales: editorial side-by-side

B
bigrquery
ANALYTICS
0.0

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.

S
scales
ANALYTICS
0.0

scales keeps widening what ggplot2 can put on an axis.

◆ Current state

scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.

◆ Where it's heading

The arc runs toward extensibility and type coverage. First came built-in support for awkward types like difftime and hms; 1.4.0 inverts that by letting any third-party class participate in range training simply by implementing range() or levels(). Labelling is getting more expressive rather than merely more numerous.

◆ Prediction

Expect continued type-support and labelling work, with extension points that let downstream packages plug in their own classes instead of scales enumerating every one.

Alternatives to bigrquery and scales

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 scales.

See all bigrquery alternatives → · See all scales alternatives →

Recent activity from bigrquery and scales

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 3mo agobigrqueryJob labels for cost allocation; microsecond upload precision
  2. 11mo agobigrqueryUses bigrquerystorage automatically for large downloads
  3. 11mo agobigrqueryDevelopment snapshot advancing 1.4.0 deprecations
  4. 1y agoscalesscales 1.4.0 opens range training to custom classes
  5. 2y agobigrqueryForward compatibility with an upcoming dbplyr release
  6. 2y agobigrqueryMIT relicensing, dbplyr second edition, full DBI support
  7. 2y agoscalesscales 1.3.0 makes timespans first-class on axes
  8. 3y agobigrquerySyncs with gargle's OAuth client rename
  9. 3y agoscalesscales 1.2.1 re-documents to fix .Rd HTML issues
  10. 4y agoscalesscales 1.2.0 fixes currency sign order and adds scale_cut
  11. 6y agoscalesscales 1.1.1 fixes palette inversion and adds oob_keep()
  12. 6y agoscalesscales 1.1.0 reorganises breaks and labels into a naming scheme

Frequently asked questions

What is the difference between bigrquery and scales?

They serve adjacent needs but don't currently overlap on shipped themes. bigrquery and scales 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 bigrquery better than scales?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bigrquery and scales 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 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 scales?

Top scales alternatives in Analytics are ranked by recent ship velocity. Browse the "scales alternatives" section above for the current picks, or visit /alternatives/scales-r for the full list with editorial commentary on each.