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meirwah
awesome-workflow-engines
Learning & Reference2019–2026
meirwah / awesome-workflow-engines

awesome-workflow-engines

A curated list of awesome open source workflow engines

7Distinct people
8Mentions
0Explicit recommenders
8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A curated list of awesome open source workflow engines

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2019-12-26 19:42:23 UTC to 2026-05-29 18:14:01 UTC.

01232019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC312
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

8 sources
Hmm I have mixed feelings about this. I've thought about this topic for a bit, a couple of years ago I thought of bringing functional reactive programming to a backend node.js project (partially because of managing callback hell); in the past couple of years I work on an event/workflow system with 100+ million events per day. This feels like a lighter weight alternative to Temporal or other workflow tools[0], but eventually for a backend system you'd likely be rebuilding features that are tailored for the backend. In frontend code, you have many side effects (e.g. DOM, styling) that rely on a single piece of data/event, and more side effects that rely on those side effects (e.g. component hierarchy), and having this laid out declaratively is one way to understand the behavior of an application when this piece of data changes. You are also
Read the rest
almost never concerned about durability/persistence of the state of data on the frontend, just because the code interacts with the browser and we almost never question the reliability of that API. A human is typically the "driver" of these interactions and is typically in the loop for most interactions, so stuff that fails, e.g. a failed network call, can bubble up to the user to deal with. Conversely, web backend projects have code and infrastructure that are distributed (even monolithic ones), and most of the time are concerned with persisting state/data, distributing/scheduling workloads, etc. Each side effect / computation, especially ones that cross networks/service, has its own requirements for whether it should be at least once/at most once, retried/retry patterns, latency/throughput, failure modes/error handling. These requirements also define your boundaries/interfaces, rather than a nice semantic and declarative one (not exclusive but oftentimes the requirements win out). Not saying that this signal-based approach can't be used in some areas of the application would benefit for declarative computation, but the examples given seem to indicate also a desire to do distributed workflow stuff. [0] https://temporal.io/, https://github.com/meirwah/awesome-workflow-engines
In The Missing Manual for Signals: State Management for Python Developers
> Koheesio is not in competition with other libraries. Yes, it is, because nobody wants to run multiple orchestrators, and the "What sets Koheesio apart from other libraries?" section does little to help users decide why they should pick yours. Workflow orchestration is a mature category, as evidenced by the length of this list: https://github.com/meirwah/awesome-workflow-engines I would expect someone who's seriously writing a new orchestrator in 2024 to cite the alternatives, their shortcomings, and how you intend to address them. Bonus points if you make a neat little table. The fact that you're leading with Python does not inspire confidence. Pretty much all workflow orchestrators use Python for their glue, and that's hardly the interesting part. What were they using at Nike before this?
In Koheesio: Nike's Python-based framework to build advanced data-pipelines

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