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collapse vs inbospatial

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

Shared themes:r-package

collapse vs inbospatial: at a glance

Featurecollapseinbospatial
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsr-package, geospatial, ogc-api, wcs
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is inbospatial?

A thin R wrapper over Flemish geospatial services, adding one standard at a time

inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.

Read the full inbospatial trajectory →

collapse vs inbospatial: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

I
inbospatial
ANALYTICS
0.0

A thin R wrapper over Flemish geospatial services, adding one standard at a time

◆ Current state

inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.

◆ Where it's heading

The package grows by absorbing one more service standard per release rather than by adding abstraction. The 0.1.0 additions point the same way — get_feature_ogc() covers a newer OGC standard alongside the existing WCS and WFS paths, and get_wcs_layers() addresses the practical problem that you cannot query a coverage without first knowing what layers exist. Release cadence is slow and driven by which service the maintainers needed next.

◆ Prediction

Expect the next release to add another regional service endpoint or extend OGC API Features coverage, on a timescale of a year or more given the gaps between the three releases so far.

Alternatives to collapse and inbospatial

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 collapse or inbospatial.

See all collapse alternatives → · See all inbospatial alternatives →

Recent activity from collapse and inbospatial

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

  1. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  2. 4mo agoinbospatialOGC API Features querying and WCS layer discovery arrive
  3. 7mo agocollapseNegative zero now hashes equal to zero across the package
  4. 8mo agocollapsecollap() no longer double-aggregates external weights
  5. 9mo agocollapseCustom unlist() preserves attributes
  6. 0y agocollapseAssorted bug fixes
  7. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  8. 1y agoinbospatialFlanders digital elevation model becomes queryable
  9. 2y agoinbospatialWMS and WMTS shorthands plus projection distortion utilities

Frequently asked questions

What is the difference between collapse and inbospatial?

Both compete on the same themes — r-package — within Analytics. collapse and inbospatial 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 collapse better than inbospatial?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collapse and inbospatial 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 collapse?

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

What are the best alternatives to inbospatial?

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