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nanoparquet vs slider

A side-by-side editorial comparison of nanoparquet and slider — release velocity, themes, recent moves, and the top alternatives to consider.

nanoparquet vs slider: at a glance

Featurenanoparquetslider
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesparquet, r-language, interoperability, data-formatssliding-windows, tidyverse, c-api-compliance, vctrs
Last editorial update1h ago51m ago
WebsiteVisit →Visit →

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.

Read the full nanoparquet trajectory →

What is slider?

Feature-complete since 2021, and every release since has been paying CRAN's C API bill

slider provides sliding-window and index-aware window functions for R, with a C implementation underneath and a specialised fast path for common aggregations. The user-facing surface has been stable since 0.3.0 in late 2022. Everything after that is compliance and platform work: STRING_PTR removed in 0.3.2, OBJECT() removed in 0.3.3, a vctrs callable's C signature corrected, and the minimum R version raised twice.

Read the full slider trajectory →

nanoparquet vs slider: editorial side-by-side

N
nanoparquet
ANALYTICS
0.0

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.

S
slider
ANALYTICS
0.0

Feature-complete since 2021, and every release since has been paying CRAN's C API bill

◆ Current state

slider provides sliding-window and index-aware window functions for R, with a C implementation underneath and a specialised fast path for common aggregations. The user-facing surface has been stable since 0.3.0 in late 2022. Everything after that is compliance and platform work: STRING_PTR removed in 0.3.2, OBJECT() removed in 0.3.3, a vctrs callable's C signature corrected, and the minimum R version raised twice.

◆ Where it's heading

Two forces set the release schedule, and neither is feature demand. The first is CRAN closing off non-API C entry points, which packages reaching into R internals for speed have to unwind one accessor at a time — slider is on its second such release with no visible loss of function. The second is vctrs, whose breaking changes slider absorbs ahead of time; 0.2.2 exists solely to prepare for one. The last release that added anything callers can see was 0.3.0's slider_plus() and slider_minus() extension hooks.

◆ Prediction

Expect the pattern to continue: another non-API accessor removal or a vctrs compatibility release, rather than new window functions. The C-level surface is the only part of this package still moving.

Alternatives to nanoparquet and slider

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 slider.

See all nanoparquet alternatives → · See all slider alternatives →

Recent activity from nanoparquet and slider

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 3mo agonanoparquet64-bit integer columns and writing Parquet to stdout
  2. 4mo agonanoparquetFiles now readable by the Java and Rust Parquet libraries
  3. 9mo agosliderNon-API OBJECT() removed and a vctrs C signature fixed
  4. 1y agonanoparquetReads Polars files that omit the dictionary page offset
  5. 1y agonanoparquetDate, FLOAT, and mixed-encoding read fixes
  6. 1y agonanoparquetSchema authoring and append_parquet arrive with a renamed API
  7. 1y agosliderNon-API STRING_PTR removed; R 4.0.0 now required
  8. 1y agonanoparquetFixes a write_parquet crash
  9. 2y agosliderValgrind test fixes and dependency version bumps
  10. 3y agosliderExtension hooks let clock and almanac types serve as an index
  11. 5y agosliderInternal vec_order usage updated ahead of a vctrs break
  12. 5y agosliderlong double alignment issue fixed for CRAN sanitisers

Frequently asked questions

What is the difference between nanoparquet and slider?

They serve adjacent needs but don't currently overlap on shipped themes. nanoparquet and slider 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 slider?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nanoparquet and slider 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 slider?

Top slider alternatives in Analytics are ranked by recent ship velocity. Browse the "slider alternatives" section above for the current picks, or visit /alternatives/slider for the full list with editorial commentary on each.