spsurvey
spsurvey has spent four years consolidating after its 5.0.0 rewrite rather than adding to it
Comparison · Analytics
dvir vs tibblify
A side-by-side editorial comparison of dvir and tibblify — release velocity, themes, recent moves, and the top alternatives to consider.
dvir vs tibblify: at a glance
What is dvir?
dvir keeps making disaster victim identification a single call instead of a workflow.
dvir handles disaster victim identification: matching unidentified remains against reference families using pedigree likelihoods. The package has consolidated around dviSolve(), a complete pipeline introduced in 3.2.1 and rewritten in 3.3.0 to use generalised likelihood ratios for families with several missing persons. Recent releases have been about making that pipeline survive large cases, adding dviGridSize() and a maxAssign cutoff to skip joint analysis when the combination count explodes, plus per-step timings.
What is tibblify?
tibblify learned to derive its own specs from OpenAPI, removing the step users disliked most
tibblify converts nested lists and JSON into rectangular tibbles using an explicit specification of the expected structure. Its 0.2.0 rewrite moved the engine to C and reset the API; 0.3.1 then added a path to generate specifications from an OpenAPI document rather than hand-writing them. 0.4.0 in May 2026 is the first release in over two years, and it is a breaking cleanup.
dvir vs tibblify: editorial side-by-side
dvir
0.0ANALYTICS
dvir keeps making disaster victim identification a single call instead of a workflow.
◆ Current state
dvir handles disaster victim identification: matching unidentified remains against reference families using pedigree likelihoods. The package has consolidated around dviSolve(), a complete pipeline introduced in 3.2.1 and rewritten in 3.3.0 to use generalised likelihood ratios for families with several missing persons. Recent releases have been about making that pipeline survive large cases, adding dviGridSize() and a maxAssign cutoff to skip joint analysis when the combination count explodes, plus per-step timings.
◆ Where it's heading
The arc is from a toolbox of functions toward one supervised pipeline, with the older jointDVI() now emitting a legacy message. The current constraint is combinatorial: joint analysis over many victims and missing persons blows up, so the work has gone to measuring the blowup and bailing out of it. Parallelism is mid-migration, with the parallel and pbapply implementation removed and a mirai replacement stated as planned but not yet shipped, leaving numCores accepted and ignored with a warning.
◆ Prediction
The mirai-based parallelisation is announced as coming, so expect it next, most likely applied to the joint analysis step that maxAssign currently exists to avoid.
tibblify
0.0ANALYTICS
tibblify learned to derive its own specs from OpenAPI, removing the step users disliked most
◆ Current state
tibblify converts nested lists and JSON into rectangular tibbles using an explicit specification of the expected structure. Its 0.2.0 rewrite moved the engine to C and reset the API; 0.3.1 then added a path to generate specifications from an OpenAPI document rather than hand-writing them. 0.4.0 in May 2026 is the first release in over two years, and it is a breaking cleanup.
◆ Where it's heading
The arc runs from 'write a spec by hand' toward 'the spec comes from somewhere else'. Alongside the OpenAPI importer, guess_tspec() gained exported variants so users can override its dispatch, and untibblify() now picks up the tib_spec attribute automatically. 0.4.0's breaking change prefixes all arguments of dot-accepting functions with a period to avoid collisions with column names, softened by a once-per-session deprecation warning, and refactors the entire codebase.
◆ Prediction
The un-dotted argument forms are explicitly slated for removal, so the next release most likely completes that deprecation. Whether the 0.4.0 refactor introduced corner-case regressions is the open question the release notes themselves raise.
Alternatives to dvir and tibblify
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 dvir or tibblify.
StreamCatTools
StreamCatTools is quietly moving off web services and onto cloud-native GeoParquet
reproducible
reproducible added a windowed read path so remote GeoTiffs never fully download
qcTAF
qcTAF is building an automated checklist for reproducible fisheries assessments, one criterion at a time
rpymat
After three dormant years, rpymat returned to fix the OpenMP crash that breaks R and conda together
ieegio
ieegio's first release lands electrode trajectory burning and a WebGL-free surface plot
See all dvir alternatives → · See all tibblify alternatives →
Recent activity from dvir and tibblify
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodvirCombination sizing and a cutoff for joint analysis
- 3mo agodvirJoint tables added to solver output
- 3mo agotibblifyFix type mismatch in C code
- 3mo agotibblifyDot-prefixed arguments and a full internal refactor
- 3mo agodvirVictim and database accessors, plus solver refinements
- 1y agodvirSolver rewritten around generalised likelihood ratios
- 2y agotibblifyparse_openapi_spec() generates tibblify specs from API documentation ⚡
- 2y agodvirdviSolve() pipeline and manual pairing controls
- 2y agodvirMaintainer handover and small reporting additions
- 3y agotibblifyRecursive specs, transform control and memory fixes
- 4y agotibblifyEngine rewritten in C with a renamed specification API ⚡
Frequently asked questions
What is the difference between dvir and tibblify?
They serve adjacent needs but don't currently overlap on shipped themes. dvir and tibblify are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is dvir better than tibblify?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dvir and tibblify are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to dvir?
Top dvir alternatives in Analytics are ranked by recent ship velocity. Browse the "dvir alternatives" section above for the current picks, or visit /alternatives/dvir for the full list with editorial commentary on each.
What are the best alternatives to tibblify?
Top tibblify alternatives in Analytics are ranked by recent ship velocity. Browse the "tibblify alternatives" section above for the current picks, or visit /alternatives/tibblify for the full list with editorial commentary on each.