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Comparison · Analytics
fastplyr vs tulpa
A side-by-side editorial comparison of fastplyr and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
fastplyr vs tulpa: at a glance
What is fastplyr?
A fast dplyr stand-in that keeps finding new places to skip work entirely.
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
What is tulpa?
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.
fastplyr vs tulpa: editorial side-by-side
fastplyr
0.0ANALYTICS
A fast dplyr stand-in that keeps finding new places to skip work entirely.
◆ Current state
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
◆ Where it's heading
The optimization strategy has shifted from making individual functions fast to reasoning about expressions before evaluating them — 0.9.9 began marking simple operators as group-unaware so expressions built only from them are evaluated across the whole data frame rather than per group. That is a structural bet: the package increasingly inspects what you wrote to decide how much work is actually needed. Running alongside it is a steady tightening of build requirements, with C++17, R 4.5.0 and CRAN's C API rules all landing within a year.
◆ Prediction
Expect the group-unaware classification to widen to more functions, since each addition compounds across every grouped expression, and expect the dependency floors to keep rising as the package tracks CRAN's compiled-code policy.
tulpa
7.5ANALYTICS
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to fastplyr and tulpa
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 fastplyr or tulpa.
Lightdash
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
Delta Lake
A 4.4.0 tag appears, but the feed carries only its release plumbing
distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio
RStudio ships through release branches, and the notes are commit messages
See all fastplyr alternatives → · See all tulpa alternatives →
Recent activity from fastplyr and tulpa
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agotulpaFirst CRAN release: engine surface unchanged from 0.0.198 ⚡
- 5d agotulpatulpa_re_aghq() exposes the mode/theta cross-Hessian
- 8d agotulpaDense batched joint path could silently drop a grid cell
- 9d agotulpaCalibration and goodness-of-fit entry points become S3 generics ⚡
- 9d agotulpaCUDA backend had two definitions; link order decided if it ran
- 9d agotulpaHyperparameter bounds now flag when they leave the node range
- 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
- 9mo agofastplyrIn-place sorting arrives with a C++17 requirement
- 11mo agofastplyrGroup-unaware expressions evaluated on the whole frame
- 1y agofastplyrf_mutate and f_reframe complete the verb set
- 1y agofastplyrDynamic argument evaluation and f_pull
- 1y agofastplyrf_fill added and grouped joins repaired
Frequently asked questions
What is the difference between fastplyr and tulpa?
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.
Is fastplyr better than tulpa?
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.
What are the best alternatives to fastplyr?
Top fastplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "fastplyr alternatives" section above for the current picks, or visit /alternatives/fastplyr for the full list with editorial commentary on each.
What are the best alternatives to tulpa?
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.