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Comparison · Analytics
mirai vs waywiser
A side-by-side editorial comparison of mirai and waywiser — release velocity, themes, recent moves, and the top alternatives to consider.
mirai vs waywiser: at a glance
What is mirai?
mirai removed its dispatcher process and added memory backpressure to the queue.
The async evaluation framework releases roughly monthly and moves fast at the architecture level. In 2.7.0 the dispatcher stopped being a separate process and became a thread, after its loop had already been rewritten in C inside nanonext one release earlier. The same release added an opt-in memory budget for queued task payloads and try_mirai(), which returns NULL immediately rather than blocking when that budget is exhausted.
What is waywiser?
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
mirai vs waywiser: editorial side-by-side
mirai
2.5ANALYTICS
mirai removed its dispatcher process and added memory backpressure to the queue.
◆ Current state
The async evaluation framework releases roughly monthly and moves fast at the architecture level. In 2.7.0 the dispatcher stopped being a separate process and became a thread, after its loop had already been rewritten in C inside nanonext one release earlier. The same release added an opt-in memory budget for queued task payloads and try_mirai(), which returns NULL immediately rather than blocking when that budget is exhausted.
◆ Where it's heading
Two threads of work run together: cutting overhead out of the task path — thread-based dispatcher, in-process transport for synchronous daemons, lower per-element dispatch cost in mirai_map() — and making the framework safe to embed in an event loop, where blocking the host R thread is not acceptable. Deployment reach is growing too, with http_config() launching remote daemons over HTTP APIs and auto-configuring for Posit Workbench. Each release pins a minimum nanonext version, so the two packages advance as one unit.
◆ Prediction
With backpressure in place but opt-in, the open question these notes leave is whether a default memory budget arrives; continued overhead reduction and Shiny-facing non-blocking paths are the safer bet.
waywiser
0.0ANALYTICS
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
◆ Current state
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
◆ Where it's heading
The package has reached the point where the interesting bugs are cross-platform and cross-package rather than statistical. Its main function, ww_multi_scale(), has been the focus of nearly every release since 0.4.0, working through units handling, aggregation ordering, raster inputs and metric-type dispatch. The dependency on vip and the tidymodels metric machinery means a share of releases exist only to track breaking changes elsewhere.
◆ Prediction
Expect the next substantive release to continue on ww_multi_scale() edge cases, given that it has absorbed most of the fixes in this window. The recent run of CRAN-compliance patches suggests no feature work is currently in flight.
Alternatives to mirai and waywiser
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 mirai or waywiser.
maplegend
The legend engine mapsf spun out, now covering legend types the parent map package can draw.
lang
R help pages translated on demand by whichever LLM you point it at.
mapsf
Thematic mapping in base R that finally got a theming system, then spent two years polishing legends.
qualtRics
qualtRics moved its contact functions onto XM Directory days before the old endpoints died.
fabletools
The tidyverts forecasting core rebuilt model combination on full residual covariance.
See all mirai alternatives → · See all waywiser alternatives →
Recent activity from mirai and waywiser
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 25d agomiraiMap collection and daemon lifecycle fixes
- 2mo agomiraiAgent skill ships in-package; HTTP headers take over auth
- 3mo agomiraiDispatcher becomes a thread, and the queue gains a memory budget ⚡
- 5mo agomiraiParallel RNG seeding leaves experimental status
- 6mo agomiraiRemote daemons over HTTP, and a C dispatcher loop
- 8mo agomiraiTelemetry span timing and daemon-switch fix
- 1y agowaywiserStops downloading data during CRAN checks
- 1y agowaywiserVignettes no longer write to CRAN directories
- 1y agowaywiserKeeps the R version floor below 4.1
- 2y agowaywiserNaN results become NA; raster metrics dispatch correctly
- 2y agowaywiserGuards against ignored grid arguments; faster on sf data
- 2y agowaywiserFixes wrong observation counts and ignored grid units
Frequently asked questions
What is the difference between mirai and waywiser?
They serve adjacent needs but don't currently overlap on shipped themes. mirai is currently shipping more aggressively (velocity 2.5 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.
Is mirai better than waywiser?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mirai is currently shipping more aggressively (velocity 2.5 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.
What are the best alternatives to mirai?
Top mirai alternatives in Analytics are ranked by recent ship velocity. Browse the "mirai alternatives" section above for the current picks, or visit /alternatives/mirai for the full list with editorial commentary on each.
What are the best alternatives to waywiser?
Top waywiser alternatives in Analytics are ranked by recent ship velocity. Browse the "waywiser alternatives" section above for the current picks, or visit /alternatives/waywiser for the full list with editorial commentary on each.