# Intel-bigdata/HiBench

HiBench is a big data benchmark suite.

Repository: https://github.com/Intel-bigdata/HiBench
Canonical: https://ross.abutalabs.com/products/hibench
Language: Java
License: NOASSERTION
License Family: other
Archived: true
Last push: 2025-12-15T16:28:33+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 57, release rhythm 8, longevity 100
- inputs: {"age_days": 5195, "days_push": 261, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1484, forks 766 (observed 2026-08-28T04:04:51.353063+00:00)

## What it is
HiBench is a big data benchmark suite with 29 workloads across micro, machine learning, SQL, graph, websearch, and streaming categories for Hadoop, Spark, and streaming frameworks. It measures speed, throughput, and system resource utilization of big data frameworks.

## Use cases
- benchmark hadoop cluster performance
- compare spark and flink throughput
- measure hdfs io throughput
- test streaming framework performance
- evaluate big data framework resource utilization
- run terasort and wordcount benchmarks

## When to choose
- you need a standard suite of big data workloads for Hadoop or Spark
- you want to compare throughput and resource usage across big data frameworks
- you need reproducible streaming benchmarks for Flink, Storm, or Spark Streaming

## When to avoid
- you need maintained or supported software - the project is archived by Intel with known security issues
- you need benchmarks for modern frameworks beyond Hadoop/Spark-era systems
- you require patches or new releases - none are accepted

## Facets
- artifact type: dataset
- maturity: abandoned
- function: benchmarking, load-testing, data-generation
- domain: big-data, performance, developer-tools
- platform: jvm, cloud
- tags: hadoop, spark, flink, storm, streaming-benchmark, archived-project, data-engineering, linux, docker

## Member repositories
- Intel-bigdata/HiBench (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:51.353063+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 2026-08-30T04:33:58.023269+00:00, confidence not recorded.
  - readme: https://github.com/Intel-bigdata/HiBench (fetched 2026-08-28T04:04:51.353063+00:00, sha 75b72c2659c5)
- Data as of 2026-08-30T08:39:29.467469+00:00.