tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
nanoparquet vs rlistings
A side-by-side editorial comparison of nanoparquet and rlistings — release velocity, themes, recent moves, and the top alternatives to consider.
nanoparquet vs rlistings: at a glance
What is nanoparquet?
nanoparquet is chasing byte-level agreement with the Java and Rust Parquet readers, not feature count.
nanoparquet reads and writes Parquet from R with no Arrow dependency, which is its entire reason to exist. The 0.4.0 line renamed the reader API and added schema authoring plus `append_parquet()`, and the 0.5.x releases have gone after interoperability: definition and repetition level encodings the Apache Parquet Java library expects, flatbuffer alignment the Rust arrow-rs reader expects, 128-bit decimals, and Polars-written files that omit the dictionary page offset. The newest release adds `bit64::integer64` columns and writing to stdout.
What is rlistings?
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.
nanoparquet vs rlistings: editorial side-by-side
nanoparquet
0.0ANALYTICS
nanoparquet is chasing byte-level agreement with the Java and Rust Parquet readers, not feature count.
◆ Current state
nanoparquet reads and writes Parquet from R with no Arrow dependency, which is its entire reason to exist. The 0.4.0 line renamed the reader API and added schema authoring plus `append_parquet()`, and the 0.5.x releases have gone after interoperability: definition and repetition level encodings the Apache Parquet Java library expects, flatbuffer alignment the Rust arrow-rs reader expects, 128-bit decimals, and Polars-written files that omit the dictionary page offset. The newest release adds `bit64::integer64` columns and writing to stdout.
◆ Where it's heading
Almost every entry since 0.4.0 names another engine — Java, arrow-rs, Polars, Arrow schema metadata — which tells you the maintainers are treating cross-reader fidelity as the product rather than R-side ergonomics. The type system is filling in from the edges: DECIMAL beyond 8 bytes, UUID, FLOAT16 and INTERVAL as raw lists, and now 64-bit integers with an explicit read-type option instead of a silent cast to double. Writing to `:stdout:` points at a second audience, shell pipelines rather than interactive R.
◆ Prediction
The remaining unmapped Parquet types the changelog has been parking in raw-vector lists — FLOAT16 and INTERVAL — are the obvious next targets, following the same pattern by which DECIMAL and UUID graduated to real R types.
rlistings
0.0ANALYTICS
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
◆ Current state
rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.
◆ Where it's heading
The package is progressively delegating pagination to formatters rather than implementing it — paginate_listing() was refactored to call formatters' paginate_to_mpfs() directly, and truetype font support arrived through a new formatters API. That reduces duplicated logic but ties the package's page-break behaviour to a dependency it shares with rtables. Feature work beyond pagination is thin: better error messages for unsupported column classes, a cheatsheet.
◆ Prediction
Expect pagination fidelity to remain the focus, with changes arriving as formatters exposes more of its layout machinery rather than as rlistings-native features.
Alternatives to nanoparquet and rlistings
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 nanoparquet or rlistings.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
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.
datasetjson
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all nanoparquet alternatives → · See all rlistings alternatives →
Recent activity from nanoparquet and rlistings
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agonanoparquet64-bit integer columns and writing Parquet to stdout
- 4mo agonanoparquetFiles now readable by the Java and Rust Parquet libraries
- 1y agonanoparquetReads Polars files that omit the dictionary page offset
- 1y agonanoparquetDate, FLOAT, and mixed-encoding read fixes
- 1y agonanoparquetSchema authoring and append_parquet arrive with a renamed API ⚡
- 1y agorlistingsError and message handling for difftime and zero-row listings
- 1y agorlistingsTrueType font support and col_gap in pagination
- 1y agonanoparquetFixes a write_parquet crash
- 2y agorlistingssplit_into_pages_by_var() and pagination moved onto formatters
Frequently asked questions
What is the difference between nanoparquet and rlistings?
They serve adjacent needs but don't currently overlap on shipped themes. nanoparquet and rlistings 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 nanoparquet better than rlistings?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nanoparquet and rlistings 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 nanoparquet?
Top nanoparquet alternatives in Analytics are ranked by recent ship velocity. Browse the "nanoparquet alternatives" section above for the current picks, or visit /alternatives/nanoparquet for the full list with editorial commentary on each.
What are the best alternatives to rlistings?
Top rlistings alternatives in Analytics are ranked by recent ship velocity. Browse the "rlistings alternatives" section above for the current picks, or visit /alternatives/rlistings for the full list with editorial commentary on each.