cmdstanr
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
Comparison · Analytics
pins vs see
A side-by-side editorial comparison of pins and see — release velocity, themes, recent moves, and the top alternatives to consider.
pins vs see: at a glance
What is pins?
pins keeps adding a storage backend per release while retiring its original API
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
What is see?
see grows wherever easystats adds a diagnostic, one plot method at a time.
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
pins vs see: editorial side-by-side
pins
0.0ANALYTICS
pins keeps adding a storage backend per release while retiring its original API
◆ Current state
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
◆ Where it's heading
Two long-running processes, neither dramatic. Backend coverage expands toward wherever teams already store artifacts, which increasingly means Databricks and cloud object storage rather than a shared drive. Meanwhile the legacy pin() API from before the board model has been in a staged deprecation across at least three releases, escalated each time rather than removed.
◆ Prediction
Expect another board or two as storage platforms are requested, and the legacy pin() functions to finally become errors; the format list will keep tracking whichever serializer the R community settles on.
see
0.0ANALYTICS
see grows wherever easystats adds a diagnostic, one plot method at a time.
◆ Current state
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
◆ Where it's heading
Growth here is downstream-driven rather than self-directed: see expands to cover new diagnostics as easystats produces them. Running alongside that is a sustained investment in presentation control — theme arguments on plot methods, elements that scale with base_size — which suits users embedding these plots in documents rather than glancing at them interactively.
◆ Prediction
Expect new plot methods to keep arriving in step with performance and parameters releases, with continued theming work rather than any change in the package's scope.
Alternatives to pins and see
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 pins or see.
comtradr
comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
billboarder
An htmlwidget whose release notes are mostly billboard.js version bumps, quiet since 2021.
bbotk
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
bayesplot
bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.
animation
Contribution-driven maintenance on a package whose last structural change was magick support.
Recent activity from pins and see
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
- 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
- 5mo agopinsqs2 replaces qs; pins can be written in multiple formats
- 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
- 11mo agoseesee 0.12.0 extends normality checks to psych factor models
- 1y agopinsPin previews on Connect; Databricks host normalization
- 1y agoseesee 0.11.0 scales theme elements with base_size
- 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
- 1y agopinsAdds board_databricks() and switches parquet to nanoparquet
- 2y agopinspin_write() arguments must be named; Connect caches removed
- 2y agopinsMessage clarity and Google Drive dribble handling
- 2y agopinsboard_gdrive() added; cache location configurable
Frequently asked questions
What is the difference between pins and see?
They serve adjacent needs but don't currently overlap on shipped themes. pins and see 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 pins better than see?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. pins and see 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 pins?
Top pins alternatives in Analytics are ranked by recent ship velocity. Browse the "pins alternatives" section above for the current picks, or visit /alternatives/pins-r for the full list with editorial commentary on each.
What are the best alternatives to see?
Top see alternatives in Analytics are ranked by recent ship velocity. Browse the "see alternatives" section above for the current picks, or visit /alternatives/see-r for the full list with editorial commentary on each.