# apache/mahout

Apache Mahout - an environment for quickly creating scalable, performant machine learning applications.

Repository: https://github.com/apache/mahout
Canonical: https://ross.abutalabs.com/products/mahout
Homepage: https://mahout.apache.org/
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: apache-mahout, cuda, python, rust, qumat-qdp, qumat
Last push: 2026-08-16T06:32:13+00:00

## Health v2 (maintenance only)
Score: 86/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 62, longevity 100
- inputs: {"age_days": 4485, "days_push": 17, "days_rel": 94, "gap_med": 118, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2304, forks 996 (observed 2026-08-28T04:06:35.597110+00:00)

## What it is
Apache Mahout is an Apache Software Foundation project providing Qumat, a high-level Python library for quantum computing with a unified API over Qiskit, Cirq, and Amazon Braket backends. It also includes QDP (Quantum Data Plane), a GPU-accelerated (CUDA/Rust) component for encoding classical data into quantum states with zero-copy tensor transfer via DLPack.

## Use cases
- build quantum circuits that run on qiskit, cirq, or amazon braket with one api
- simulate quantum algorithms like grover or deutsch-jozsa in python
- encode classical data into quantum states on gpu for quantum machine learning
- move tensors between pytorch, numpy, and tensorflow without copying
- learn quantum computing with a python primer and notebooks
- run parameterized quantum circuits on simulators or real quantum hardware

## When to choose
- you want a backend-agnostic quantum circuit API so you can switch between Qiskit, Cirq, and Braket
- you need GPU-accelerated data encoding for quantum ML pipelines with zero-copy tensor exchange
- you prefer an Apache-licensed library with active community and monthly releases

## When to avoid
- you need mature classical ML algorithms like the old Mahout recommender/clustering stack, which is no longer the focus
- you require a production-hardened quantum SDK with extensive algorithm coverage beyond basic gates
- you don't have an NVIDIA GPU and need QDP's accelerated data encoding

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, sdk, gpu-computing, simulation
- domain: quantum-computing, machine-learning, artificial-intelligence
- platform: python, cross-platform
- tags: quantum-computing, quantum-circuits, quantum-machine-learning, qiskit, cirq, amazon-braket, cuda, dlpack, rust-kernels, gpu

## Member repositories
- apache/mahout (main) score 86

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:35.597110+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 2026-08-30T02:39:43.176353+00:00, confidence not recorded.
  - readme: https://github.com/apache/mahout (fetched 2026-08-28T04:06:35.597110+00:00, sha 43ac486aa992)
  - homepage: https://mahout.apache.org/ (fetched 2026-08-29T10:20:14.439789+00:00, sha 93a016b5a829)
  - site_page: https://mahout.apache.org/docs/about/how-to-contribute (fetched 2026-08-29T10:20:14.448736+00:00, sha 516896444d5a)
  - site_page: https://mahout.apache.org/docs/qumat (fetched 2026-08-29T10:20:14.450774+00:00, sha 1ca0d00997ac)
  - site_page: https://mahout.apache.org/docs/qumat/getting-started (fetched 2026-08-29T10:20:14.452413+00:00, sha 4b30cf3c6d2c)
  - site_page: https://mahout.apache.org/docs/qdp (fetched 2026-08-29T10:20:14.453895+00:00, sha 7af12b29e00c)
  - site_page: https://mahout.apache.org/docs/learning/quantum-computing-primer (fetched 2026-08-29T10:20:14.455346+00:00, sha 3439aab961ef)
  - site_page: https://mahout.apache.org/docs/learning/papers (fetched 2026-08-29T10:20:14.456858+00:00, sha 316e5e4d7c71)
  - site_page: https://mahout.apache.org/docs/community (fetched 2026-08-29T10:20:14.458306+00:00, sha 114c1a7789e3)
  - site_page: https://mahout.apache.org/docs/community/who-we-are (fetched 2026-08-29T10:20:14.459799+00:00, sha 04a438d96542)
- Data as of 2026-08-30T08:39:29.467469+00:00.