# Rdatatable/data.table

R's data.table package extends data.frame:

Repository: https://github.com/Rdatatable/data.table
Canonical: https://ross.abutalabs.com/products/datatable
Homepage: http://r-datatable.com
Language: R
License: MPL-2.0
License Family: copyleft
Last push: 2026-08-25T15:38:04+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 4470, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3913, forks 1051 (observed 2026-08-28T04:08:28.869695+00:00)

## What it is
data.table is an R package providing a high-performance, memory-efficient replacement for base R's data.frame with a concise indexing syntax. It includes fast file reading/writing (fread/fwrite), parallelized aggregation, rich joins, and reference-based column updates.

## Use cases
- fast csv reading in r
- aggregate billions of rows quickly
- join two large tables in r
- pivot and unpivot data
- update columns by reference without copying
- replace dplyr for speed on large data

## When to choose
- working with large datasets in R where base data.frame or dplyr is too slow or memory hungry
- you need fast delimited file I/O, joins, or reshaping
- you want a dependency-free, mature package for production R code

## When to avoid
- you are not working in R
- your team prefers dplyr/tidyverse pipe syntax and readability over raw speed
- data does not fit in memory and you need out-of-core or distributed processing

## Facets
- artifact type: library
- maturity: stable
- function: data-science, etl, csv, serialization
- domain: data-science, analytics, big-data
- platform: cross-platform
- tags: r-package, dataframe, fast-csv, in-memory-data, joins, reshaping, data-engineering, r

## Member repositories
- Rdatatable/data.table (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:28.869695+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 2026-08-29T18:25:03.919419+00:00, confidence not recorded.
  - readme: https://github.com/Rdatatable/data.table (fetched 2026-08-28T04:08:28.869695+00:00, sha 466f4d2e30ed)
  - homepage: http://r-datatable.com (fetched 2026-08-29T09:18:59.304775+00:00, sha be703be71139)
  - site_page: https://r-datatable.com/articles/datatable-faq.html (fetched 2026-08-29T09:18:59.339412+00:00, sha 6594fdf36dfa)
- Data as of 2026-08-30T08:39:29.467469+00:00.