tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and git2rdata — release velocity, themes, recent moves, and the top alternatives to consider.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
git2rdata keeps sharpening one idea: a data frame that produces a readable git diff.
git2rdata stores data frames as plain text plus a metadata sidecar so that version control sees meaningful line-level diffs instead of binary churn. The recent releases have all pushed on the metadata half of that pair: 0.4.1 added `update_metadata()`, 0.5.1 made arbitrary data frame metadata round-trip through storage, and 0.5.2 adds a `convert` argument that records column conversions in the metadata and reverses them on read.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.
The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.
git2rdata stores data frames as plain text plus a metadata sidecar so that version control sees meaningful line-level diffs instead of binary churn. The recent releases have all pushed on the metadata half of that pair: 0.4.1 added `update_metadata()`, 0.5.1 made arbitrary data frame metadata round-trip through storage, and 0.5.2 adds a `convert` argument that records column conversions in the metadata and reverses them on read.
The file format itself settled years ago — the last breaking change was the 0.2.0 hash rework — and development since has been about what travels alongside the data. Storage decisions that used to be implicit are becoming declarative and recorded: significant digits in 0.5.0, arbitrary attributes in 0.5.1, type conversions in 0.5.2. The other steady thread is determinism, from C-locale sorting through `icuSetCollate()`, because unstable ordering is what turns a one-row change into a whole-file diff.
The metadata system has absorbed digits, attributes and conversions in three consecutive releases, so the next likely addition is another storage decision moved into metadata rather than any change to the on-disk format.
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 datasetjson or git2rdata.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all datasetjson alternatives → · See all git2rdata alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. datasetjson and git2rdata 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. datasetjson and git2rdata 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.
Top datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson for the full list with editorial commentary on each.
Top git2rdata alternatives in Analytics are ranked by recent ship velocity. Browse the "git2rdata alternatives" section above for the current picks, or visit /alternatives/git2rdata for the full list with editorial commentary on each.