tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
nanoparquet vs r2rtf
A side-by-side editorial comparison of nanoparquet and r2rtf — release velocity, themes, recent moves, and the top alternatives to consider.
nanoparquet vs r2rtf: 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 r2rtf?
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.
nanoparquet vs r2rtf: 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.
r2rtf
0.0ANALYTICS
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
◆ Current state
r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.
◆ Where it's heading
Two threads run through the window. One is output reach: RTF remains the composition target, but the artifacts that come out of it now include DOCX and HTML, and page numbering can be made table-relative across multi-page tables. The other is durability under a moving R and font stack — the ANSI/Unicode converter was rebuilt, the LaTeX mapping table generated from code rather than shipped as sysdata, unlist() usage fixed for R 4.5, and graphics-device leaks that produced stray Rplots.pdf closed off.
◆ Prediction
Having exported DOCX and HTML conversion, the likely next step is filling in what those formats lose relative to RTF — pagination and footnote fidelity are the obvious gaps. The i18n path currently covers Chinese only, so additional font families are the other plausible direction.
Alternatives to nanoparquet and r2rtf
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 r2rtf.
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 nanoparquet alternatives → · See all r2rtf alternatives →
Recent activity from nanoparquet and r2rtf
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
- 7mo agor2rtfDOCX and HTML output become exported functions
- 11mo agor2rtfChinese character support arrives via an i18n font path ⚡
- 1y agor2rtfText colour fixed for figures encoded into RTF
- 1y agor2rtfFootnote handling fixed for R 4.5.0
- 1y agonanoparquetReads Polars files that omit the dictionary page offset
- 1y agor2rtfUnicode converter rebuilt and mapping table made inspectable
- 1y agonanoparquetDate, FLOAT, and mixed-encoding read fixes
- 1y agonanoparquetSchema authoring and append_parquet arrive with a renamed API ⚡
- 1y agonanoparquetFixes a write_parquet crash
- 2y agor2rtfUTF-8 conversion fix and LibreOffice 7.6 support
Frequently asked questions
What is the difference between nanoparquet and r2rtf?
They serve adjacent needs but don't currently overlap on shipped themes. nanoparquet and r2rtf 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 r2rtf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nanoparquet and r2rtf 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 r2rtf?
Top r2rtf alternatives in Analytics are ranked by recent ship velocity. Browse the "r2rtf alternatives" section above for the current picks, or visit /alternatives/r2rtf for the full list with editorial commentary on each.