# TimelyDataflow/timely-dataflow

A modular implementation of timely dataflow in Rust

Repository: https://github.com/TimelyDataflow/timely-dataflow
Canonical: https://ross.abutalabs.com/products/timely-dataflow
Language: Rust
License: MIT
License Family: permissive
Last push: 2026-08-19T01:33:49+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 98, release rhythm 81, longevity 100
- inputs: {"age_days": 4287, "days_push": 15, "days_rel": 50, "gap_med": 0, "n_releases_24m": 112}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3642, forks 293 (observed 2026-08-28T04:08:12.853199+00:00)

## What it is
A modular Rust implementation of the timely dataflow computational model from the Naiad paper, providing a low-latency cyclic data-parallel compute engine. The same program scales from a single thread on a laptop to distributed execution across a cluster.

## Use cases
- build low-latency streaming dataflow pipelines in Rust
- scale a data-parallel program from one thread to a cluster
- implement incremental and cyclic graph computations
- prototype distributed stream processing algorithms
- process large datasets with high-throughput parallel operators

## When to choose
- you need expressive, low-latency cyclic dataflow computation in Rust
- you want one program that scales from laptop to cluster
- you are building stream processing systems or research compute engines

## When to avoid
- you need a turnkey streaming system with connectors and SQL rather than a compute framework
- your team is not comfortable with Rust and dataflow programming
- you only need simple batch ETL with existing tooling

## Facets
- artifact type: library
- maturity: active
- function: streaming, concurrency, data-science, etl
- domain: microservices, big-data
- platform: rust, windows, cross-platform
- tags: dataflow, naiad, data-parallel, low-latency, distributed-compute, data-engineering, real-time, linux, macos

## Member repositories
- TimelyDataflow/timely-dataflow (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:12.853199+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 2026-08-29T18:31:46.918930+00:00, confidence not recorded.
  - readme: https://github.com/TimelyDataflow/timely-dataflow (fetched 2026-08-28T04:08:12.853199+00:00, sha 0ca000641c84)
- Data as of 2026-08-30T08:39:29.467469+00:00.