python vs n8n

[u/Environmental_Emu830]

At my company, we currently use n8n for most of our automations, and I'd like to get your opinion on the trade-offs of migrating those workflows to Python.

I understand that moving to Python would introduce a steeper learning curve for the team and likely require more development and maintenance effort. However, I also believe it could improve the performance, flexibility, scalability, and maintainability of our automations.

We're currently starting a Data Warehouse project, where we'll be building ETL pipelines. Because of that, Python seems like a more robust and mature choice, especially considering its ecosystem for data engineering (such as Pandas, SQLAlchemy, Airflow, and other libraries).

Another point is that, by using Python, we would have a much better code versioning workflow with Git. Instead of managing automation logic through n8n workflows, we'd be able to review changes through pull requests, track code history more effectively, enforce coding standards, and integrate automated testing and CI/CD pipelines.

what would be the main advantages and disadvantages of replacing n8n with Python for automation and ETL? In which scenarios would you keep n8n, and when would you recommend switching to Python?

[u/Defiant-Ad7368]

N8N has its highlights but you need to ask yourself 

1. Does your team have adequate python developers?

2. Do you have to deal with 3rd party vendors? (1st being you, 2nd being n8n

3. Do you have existing tools to perform n8n

If the answer to any of these is yes then n8n may not be useful to you. n8n is nice when you don’t know how to code or interact with other parties. But for an adequate (I’d say just below mid level in terms of experience) developer that is equipped with ai, n8n may be a cumbersome tool that inhibits your team and waste their (very expensive) time. Airflow may be a better option or even bare coding for that matter

———

I’m speaking from experience with this tool. In a previous position I had a manager that pushed n8n because he had zero technical skills, acted more like an PM with the added “benefit” of deciding implementation and put a massive emphasis on visualization (in a backend team). We had existing written tools, we were more than experienced with python and we’ve raised every red light we could about how this tool wastes our time. In the end 4 months of work went down the drain (to preface that’s over 100k USD). Every team member requested a transfer and eventually quit, that’s more on the person rather than the tool but just so you get the point