HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
ggdist vs nfs-ganesha
A side-by-side editorial comparison of ggdist and nfs-ganesha — release velocity, themes, recent moves, and the top alternatives to consider.
ggdist vs nfs-ganesha: at a glance
What is ggdist?
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
What is nfs-ganesha?
NFS-Ganesha is porting its management plane from DBUS to gRPC, four major versions in a month.
NFS-Ganesha is a user-space NFS server with pluggable FSAL backends for CEPH, GPFS and others. It is releasing major versions at an unusual rate — 12.0 through 15.1 since mid-July — and the connecting thread across all of them is gRPC: infrastructure first, then stats collection ported from DBUS, then more commands, then CacheMgr APIs and export management. Version 15.0 adds memory statistics and accounting alongside those APIs.
ggdist vs nfs-ganesha: editorial side-by-side
ggdist
0.0INFRA · APIS
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
◆ Current state
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
◆ Where it's heading
Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.
◆ Prediction
Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.
nfs-ganesha
6.3INFRA · APIS
NFS-Ganesha is porting its management plane from DBUS to gRPC, four major versions in a month.
◆ Current state
NFS-Ganesha is a user-space NFS server with pluggable FSAL backends for CEPH, GPFS and others. It is releasing major versions at an unusual rate — 12.0 through 15.1 since mid-July — and the connecting thread across all of them is gRPC: infrastructure first, then stats collection ported from DBUS, then more commands, then CacheMgr APIs and export management. Version 15.0 adds memory statistics and accounting alongside those APIs.
◆ Where it's heading
This is a control-plane migration carried out release by release in the open. Each version moves another slice of management surface onto gRPC — stats, exports, cache manager, a fake recall API for testing — while the data path work continues separately with XCOPY and clustered quality of service at 14.0. The 15.1 release extends ShowExports with a protocol summary and adds a gRPC FakeRecall API, which reads as filling in coverage rather than opening new ground. Note 15.0 and 15.1 are stamped seventy-nine seconds apart, so they were cut together rather than released as separate events.
◆ Prediction
Expect the remaining DBUS-era management commands to keep landing as gRPC APIs at this cadence. The open question these entries do not answer is whether DBUS is eventually removed or kept indefinitely alongside.
Alternatives to ggdist and nfs-ganesha
Other Infra & APIs 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 ggdist or nfs-ganesha.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
finnts
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all ggdist alternatives → · See all nfs-ganesha alternatives →
Recent activity from ggdist and nfs-ganesha
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agonfs-ganeshaShowExports gains a protocol summary; gRPC FakeRecall API added
- 1d agonfs-ganeshaMemory accounting and CacheMgr gRPC APIs
- 13d agonfs-ganeshaMore gRPC commands and RDMA rpcbind registration
- 15d agonfs-ganeshaXCOPY server-side copy and clustered quality of service ⚡
- 24d agonfs-ganeshagRPC expands with more stats collection
- 1mo agonfs-ganeshagRPC stats collection ported over from DBUS
- 1y agoggdistPer-geometry thickness subscales and settable defaults
- 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator ⚡
- 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
- 3y agoggdistBounded density becomes the default; existing charts change ⚡
- 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
- 4y agoggdistComputed variables shared across sub-geometries
Frequently asked questions
What is the difference between ggdist and nfs-ganesha?
They serve adjacent needs but don't currently overlap on shipped themes. nfs-ganesha is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 ggdist better than nfs-ganesha?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nfs-ganesha is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to ggdist?
Top ggdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggdist alternatives" section above for the current picks, or visit /alternatives/ggdist for the full list with editorial commentary on each.
What are the best alternatives to nfs-ganesha?
Top nfs-ganesha alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "nfs-ganesha alternatives" section above for the current picks, or visit /alternatives/nfs-ganesha for the full list with editorial commentary on each.