# chrislusf/gleam

Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.

Repository: https://github.com/chrislusf/gleam
Canonical: https://ross.abutalabs.com/products/chrislusf-gleam
Language: Go
License: Apache-2.0
License Family: permissive
Topics: distributed-computing, map-reduce, golang, distributed-systems
Last push: 2026-07-25T02:20:34+00:00

## Health v2 (maintenance only)
Score: 75/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 94, release rhythm 35, longevity 100
- inputs: {"age_days": 3659, "days_push": 40, "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 3562, forks 292 (observed 2026-08-28T04:08:09.829262+00:00)

## What it is
Gleam is a fast, efficient distributed map/reduce execution system written in pure Go, defining computations as DAG flows that can run standalone or across a cluster. It supports in-memory or on-disk data flow, with user computations written in Go, Unix pipe tools, or any streaming programs.

## Use cases
- run distributed map/reduce jobs in Go
- build ETL data pipelines with DAG execution
- process large datasets in memory or on disk
- execute data flows across a cluster of machines
- replace JVM-based big data frameworks with a lightweight Go alternative
- chain Unix command-line tools into distributed pipelines

## When to choose
- you want a lightweight, memory-efficient distributed data processing system in pure Go
- you need DAG-based map/reduce execution that scales from a single machine to a cluster
- you want to mix Go code with Unix streaming tools in one pipeline

## When to avoid
- you need a mature ecosystem with SQL, rich connectors, and large community support like Spark or Flink
- your workloads are small enough that a simple script suffices
- you need non-Go language SDKs beyond streaming programs

## Facets
- artifact type: library
- maturity: active
- function: etl, streaming, concurrency, workflow-automation
- domain: microservices, big-data, developer-tools
- platform: windows, go, cross-platform
- tags: map-reduce, dag-execution, distributed-computing, data-pipeline, unix-pipes, data-engineering, linux, macos

## Member repositories
- chrislusf/gleam (main) score 75

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:09.829262+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 2026-08-29T18:34:12.447442+00:00, confidence not recorded.
  - readme: https://github.com/chrislusf/gleam (fetched 2026-08-28T04:08:09.829262+00:00, sha ca944071aafd)
- Data as of 2026-08-30T08:39:29.467469+00:00.