# apache/arrow-rs

Official Rust implementation of Apache Arrow

Repository: https://github.com/apache/arrow-rs
Canonical: https://ross.abutalabs.com/products/arrow-rs
Homepage: https://arrow.apache.org/
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: arrow, parquet
Last push: 2026-08-26T21:50:33+00:00

## Health v2 (maintenance only)
Score: 98/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 96, longevity 100
- inputs: {"age_days": 1964, "days_push": 7, "days_rel": 27, "gap_med": 15, "n_releases_24m": 32}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3592, forks 1281 (observed 2026-08-28T04:08:11.208671+00:00)

## What it is
The official Rust implementation of Apache Arrow, providing the in-memory columnar format, and of Apache Parquet for columnar file reading and writing. It ships as a set of crates including core arrow arrays, compute kernels, IPC, CSV/JSON support, and the parquet crate.

## Use cases
- read and write parquet files in rust
- columnar in-memory data processing
- zero-copy data interchange between processes
- build analytical query engines in rust
- convert csv and json to arrow record batches
- efficient data transfer between rust and python via arrow

## When to choose
- you need fast, memory-efficient columnar data processing in Rust
- you are reading or writing Parquet files
- you want zero-copy interoperability with other Arrow implementations like PyArrow
- you are building data infrastructure such as query engines or ETL pipelines in Rust

## When to avoid
- you just need simple row-based data handling with small datasets
- you need the full C++ feature set such as Flight SQL or Gandiva
- your project is not in Rust and native bindings exist for your language

## Facets
- artifact type: library
- maturity: active
- function: serialization, parser, data-science, etl
- domain: databases, big-data, analytics, developer-tools
- platform: rust, cross-platform
- tags: apache-arrow, parquet, columnar-format, in-memory-analytics, zero-copy, dataframes, data-engineering

## Member repositories
- apache/arrow-rs (main) score 98

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:11.208671+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:33:50.595843+00:00, confidence not recorded.
  - readme: https://github.com/apache/arrow-rs (fetched 2026-08-28T04:08:11.208671+00:00, sha 35263ca8bfab)
  - homepage: https://arrow.apache.org/ (fetched 2026-08-29T09:27:18.245094+00:00, sha 6d4fe8b813e4)
  - site_page: https://arrow.apache.org/install (fetched 2026-08-29T09:27:18.257069+00:00, sha 49746bd5a01f)
  - site_page: https://arrow.apache.org/docs (fetched 2026-08-29T09:27:18.260817+00:00, sha 019af2cc6d05)
  - site_page: https://arrow.apache.org/docs/format/Columnar.html (fetched 2026-08-29T09:27:18.262695+00:00, sha 1865d8487754)
  - site_page: https://arrow.apache.org/docs/c_glib (fetched 2026-08-29T09:27:18.265976+00:00, sha f10a4eb11b9b)
  - site_page: https://arrow.apache.org/docs/cpp (fetched 2026-08-29T09:27:18.273558+00:00, sha c6752d031e57)
  - site_page: https://arrow.apache.org/docs/python (fetched 2026-08-29T09:27:18.275315+00:00, sha 7bf112b1dd74)
  - site_page: https://arrow.apache.org/faq (fetched 2026-08-29T09:27:18.254173+00:00, sha 23376e75a49d)
  - site_page: https://arrow.apache.org/release (fetched 2026-08-29T09:27:18.259042+00:00, sha 052acd09a846)
- Data as of 2026-08-30T08:39:29.467469+00:00.