dbt Core
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
A side-by-side editorial comparison of ggmapinset and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
A ggplot2 inset-map extension that is now infrastructure for other packages
ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.
The package has moved steadily from feature to foundation. 0.3.0 replaced confusing parameter names and rebuilt everything on stat_sf_inset() so coordinate limits stayed correct, then exposed transform_to_inset() explicitly for extension developers. 0.4.0 generalised inset shapes beyond circles to rectangles and arbitrary sf geometries. 0.5.0 continues in that direction, changing defaults in ways that require downstream extensions to adapt — the cost of being depended upon.
Expect further extension points driven by what ggautomap and the other cidm-ph mapping packages need, with the user-facing inset API staying largely settled after the shape generalisation.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.
Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.
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 ggmapinset or tulpa.
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics keeps fencing in the AI layer it spent the summer building.
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
AgencyAI got skills three weeks ago; everything since has been making them routine.
Interfaces gets the permissions layer it needed, one release after launching.
See all ggmapinset alternatives → · See all tulpa alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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 ggmapinset alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmapinset alternatives" section above for the current picks, or visit /alternatives/ggmapinset for the full list with editorial commentary on each.
Top tulpa alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpa alternatives" section above for the current picks, or visit /alternatives/tulpa for the full list with editorial commentary on each.