qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of dbt Core and quantities — release velocity, themes, recent moves, and the top alternatives to consider.
dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
dbt-core maintains an unusually wide set of live branches, and on August 14 it cut releases for 1.1 through 1.8 in a single day. Every one of them carries the same single feature: a warning when the user is running a deprecated dbt version. The older branches picked up a few long-standing backports alongside it — semver comparison, JSON log formatting, seeds from stored manifest data — and 1.4 through 1.6 dropped Python 3.8 testing now that it is end of life.
The glue package that makes R carry units and uncertainty through the same calculation.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
dbt-core maintains an unusually wide set of live branches, and on August 14 it cut releases for 1.1 through 1.8 in a single day. Every one of them carries the same single feature: a warning when the user is running a deprecated dbt version. The older branches picked up a few long-standing backports alongside it — semver comparison, JSON log formatting, seeds from stored manifest data — and 1.4 through 1.6 dropped Python 3.8 testing now that it is end of life.
This is a coordinated deprecation campaign rather than product work. Shipping the same warning to every ancient branch at once is how a maintainer starts reclaiming a support surface, and the parallel removal of Python 3.8 support points the same way. The actual development is happening on 1.11 and 1.12, where recent releases sync JSON schemas from dbt-fusion and fix adapter config recognition — the branch where the Fusion engine transition is visible.
Expect formal end-of-life announcements for the branches that just received the warning, and continued dbt-fusion schema convergence on 1.12. The backport waves should thin out once the deprecated branches are formally retired.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.
Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.
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 dbt Core or quantities.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all dbt Core alternatives → · See all quantities alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 7.5 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 7.5 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.
Top dbt Core alternatives in Analytics are ranked by recent ship velocity. Browse the "dbt Core alternatives" section above for the current picks, or visit /alternatives/dbt-core for the full list with editorial commentary on each.
Top quantities alternatives in Analytics are ranked by recent ship velocity. Browse the "quantities alternatives" section above for the current picks, or visit /alternatives/quantities for the full list with editorial commentary on each.