rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of dbt Core and epiflows — 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.
epiflows has shipped four releases in eight years, none of which changed the code.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
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.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
The package is being kept installable rather than developed. The one recent release is dependency maintenance contributed from outside, which is the pattern for RECON-era epidemiology packages that have outlived their original project funding. Two separate entries are both labelled version 0.2.1, so even the version history is not a reliable guide to what changed.
Any further releases will most likely be more deprecation cleanup to keep the package on CRAN; there is nothing in the record suggesting active development has resumed.
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 epiflows.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all dbt Core alternatives → · See all epiflows 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 epiflows alternatives in Analytics are ranked by recent ship velocity. Browse the "epiflows alternatives" section above for the current picks, or visit /alternatives/epiflows-r for the full list with editorial commentary on each.