tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
daiquiri vs datapack
A side-by-side editorial comparison of daiquiri and datapack — release velocity, themes, recent moves, and the top alternatives to consider.
daiquiri vs datapack: at a glance
What is daiquiri?
A data-quality report generator that finished its API rewrite and has been coasting on small features since.
daiquiri turns a raw clinical or administrative dataset into an HTML report of time-series data-quality plots, driven by a field-type specification the user writes. The public API settled in 2022 after a wholesale rename for rOpenSci acceptance, and releases since then have added specification conveniences rather than new report content. The 1.2.0 release is the first in nearly two years.
What is datapack?
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
daiquiri vs datapack: editorial side-by-side
daiquiri
0.0ANALYTICS
A data-quality report generator that finished its API rewrite and has been coasting on small features since.
◆ Current state
daiquiri turns a raw clinical or administrative dataset into an HTML report of time-series data-quality plots, driven by a field-type specification the user writes. The public API settled in 2022 after a wholesale rename for rOpenSci acceptance, and releases since then have added specification conveniences rather than new report content. The 1.2.0 release is the first in nearly two years.
◆ Where it's heading
Development has shifted from restructuring the interface to lowering the cost of using it — field_types_advanced() lets users name only the columns they care about and default the rest, which is the kind of change that matters when a dataset has hundreds of fields. Plot rendering is getting incremental attention (heatmap scaling) rather than new visualisation types. Cadence is roughly annual.
◆ Prediction
Expect the next release to continue trimming specification boilerplate for wide datasets rather than adding report sections; the entries give no indication of a new plot type or output format in progress.
datapack
0.0ANALYTICS
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
◆ Current state
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
◆ Where it's heading
The arc runs from assembly to correctness of the resulting archive. Later releases keep tightening the metadata the resource map must carry — dc:creator always present, dcterms:modified always updated, the package correctly flagged as modified after any access-policy change — because a bundle whose provenance record is subtly wrong is worse than one that fails outright. The three-year gap between 1.4.1 and 1.4.2, and the latter's CRAN-note content, place this package firmly in preservation.
◆ Prediction
Expect the next release, if any, to be another CRAN-compliance patch rather than functional work. The 1.4.2 note that it contains no new features is the clearest statement in the feed about where this package sits.
Alternatives to daiquiri and datapack
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 daiquiri or datapack.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all daiquiri alternatives → · See all datapack alternatives →
Recent activity from daiquiri and datapack
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agodatapackCRAN documentation and CI cleanup
- 1y agodaiquirifield_types_advanced() lets specs name only some columns
- 3y agodaiquirift_strata() splits reports by a column's values
- 3y agodaiquiriColumn-order and integer-column validation fixes
- 3y agodaiquiriReport intermediates write to tempdir(), not the library
- 3y agodaiquiriFirst CRAN release
- 3y agodaiquiriPublic API renamed wholesale for rOpenSci acceptance ⚡
- 4y agodatapackBagIt serialisation brought in line with the current spec
- 5y agodatapackSHA-256 becomes the default checksum algorithm
- 6y agodatapackResource map metadata guaranteed; removeRelationships() added
- 8y agodatapackupdateMetadata no longer drops package relationships
- 9y agodatapackAssembled data packages become editable in place ⚡
Frequently asked questions
What is the difference between daiquiri and datapack?
They serve adjacent needs but don't currently overlap on shipped themes. daiquiri and datapack 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 daiquiri better than datapack?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. daiquiri and datapack 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 daiquiri?
Top daiquiri alternatives in Analytics are ranked by recent ship velocity. Browse the "daiquiri alternatives" section above for the current picks, or visit /alternatives/daiquiri for the full list with editorial commentary on each.
What are the best alternatives to datapack?
Top datapack alternatives in Analytics are ranked by recent ship velocity. Browse the "datapack alternatives" section above for the current picks, or visit /alternatives/datapack for the full list with editorial commentary on each.