Over the past few weeks, I’ve been working extensively with n8n — building WebSocket connections, integrating different databases, creating AI agents including parsing of JSON, connecting to messengers, and moving data back and forth between systems. This hands-on experience gave me a solid basis to compare n8n with KNIME, a tool I’ve been using for a long time.
And I have to say: n8n is incredibly impressive when it comes to connectivity.
With just a few clicks, you can connect messengers, APIs, databases, create webhooks and start exchanging data almost immediately. This level of simplicity and speed in setting up integrations is something KNIME, in my view, cannot match. The user interface is also very intuitive and pleasant to work with (of course, that’s partly a matter of taste).
However, once you move beyond simple data transfers, a clear trade-off becomes visible.
In n8n, as soon as data processing becomes more complex, you quickly find yourself switching into JavaScript or Python. Although there is a graphical interface, meaningful data manipulation often requires coding.
This is where KNIME shows its real strength.
KNIME allows you to work with data at a much higher level using graphical programming. You can transform, enrich, aggregate, and deeply inspect data without writing code. The overall data handling capabilities are significantly more powerful and transparent. Especially when datasets grow larger and workflows become more complex, KNIME provides far better visibility and control.
Another important aspect is debugging.
As long as n8n workflows deal with small JSON payloads moving between services, everything remains manageable. But as soon as data volume increases, understanding what is happening inside the workflow becomes much harder. KNIME, on the other hand, excels at making data visible at every step of the process.
Finally, there is the topic of parallelization and performance.
n8n workflows essentially run sequentially on a single core, whereas KNIME is designed to handle larger data workloads more efficiently.
My conclusion is:
-
n8n is outstanding for integration, automation, and connecting systems quickly.
-
KNIME is superior for data processing, analysis, transparency, and scalability.
Both tools are excellent — but they shine in very different domains.
