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fellingdater vs mirai

A side-by-side editorial comparison of fellingdater and mirai — release velocity, themes, recent moves, and the top alternatives to consider.

fellingdater vs mirai: at a glance

Featurefellingdatermirai
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesdendrochronology, crossdating, archaeology, ropensciparallel-computing, async, backpressure, shiny
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is fellingdater?

Went from estimating felling dates to doing the crossdating that produces them.

fellingdater estimates when a tree was felled from sapwood measurements, the core inference in dendrochronological dating of timber. Version 1.0.0 passed rOpenSci review with that scope, and the 2024 releases were mostly about the accompanying JOSS paper and user-supplied sapwood datasets. Version 1.2.0 changed the package's remit substantially, adding an entire trs_* family for tree-ring series handling: crossdating with multiple statistical measures, the Hollstein and Baillie-Pilcher t-value transformations, parallel variation percentages, synthetic series generation, and dated-series plotting.

Read the full fellingdater trajectory →

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.

Read the full mirai trajectory →

fellingdater vs mirai: editorial side-by-side

F
fellingdater
ANALYTICS
0.0

Went from estimating felling dates to doing the crossdating that produces them.

◆ Current state

fellingdater estimates when a tree was felled from sapwood measurements, the core inference in dendrochronological dating of timber. Version 1.0.0 passed rOpenSci review with that scope, and the 2024 releases were mostly about the accompanying JOSS paper and user-supplied sapwood datasets. Version 1.2.0 changed the package's remit substantially, adding an entire trs_* family for tree-ring series handling: crossdating with multiple statistical measures, the Hollstein and Baillie-Pilcher t-value transformations, parallel variation percentages, synthetic series generation, and dated-series plotting.

◆ Where it's heading

The package has expanded backwards along the workflow. It began at the last step — given dated series, estimate the felling date — and 1.2.0 added the step before it, establishing those dates by crossdating in the first place. Version 1.2.1 is early polish on that new surface: axis control, non-syntactic column names, encoding safety in read_fh(). The direction is a single package covering the chain from raw ring widths to a felling-date estimate.

◆ Prediction

Expect the trs_* family to keep accumulating polish and additional crossdating statistics, since it is barely a year old and 1.2.1 was already fixing its plotting and top_n behaviour. Whether the two halves of the package get unified into one workflow interface is the open question the entries do not answer.

M
mirai
ANALYTICS
2.5

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.

Alternatives to fellingdater and mirai

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 fellingdater or mirai.

See all fellingdater alternatives → · See all mirai alternatives →

Recent activity from fellingdater and mirai

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 25d agomiraiMap collection and daemon lifecycle fixes
  2. 2mo agomiraiAgent skill ships in-package; HTTP headers take over auth
  3. 3mo agomiraiDispatcher becomes a thread, and the queue gains a memory budget
  4. 4mo agofellingdaterPolish for the crossdating plots and file reader
  5. 5mo agomiraiParallel RNG seeding leaves experimental status
  6. 6mo agomiraiRemote daemons over HTTP, and a C dispatcher loop
  7. 8mo agomiraiTelemetry span timing and daemon-switch fix
  8. 1y agofellingdaterAdds a full crossdating and tree-ring analysis toolkit
  9. 1y agofellingdaterUser-supplied sapwood data works across all functions
  10. 1y agofellingdaterFixes fd_report() with user-defined sapwood files
  11. 2y agofellingdaterJOSS paper accepted; citation updated
  12. 2y agofellingdaterAdds a workflow vignette ahead of JOSS submission

Frequently asked questions

What is the difference between fellingdater and mirai?

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 fellingdater better than mirai?

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 fellingdater?

Top fellingdater alternatives in Analytics are ranked by recent ship velocity. Browse the "fellingdater alternatives" section above for the current picks, or visit /alternatives/fellingdater for the full list with editorial commentary on each.

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.