I am completely new to KNIME but I have been told that is a good software for data analysis, so I am keen to make use of it.

But I am much more familiar with MATLAB, therefore I would like to know the advantages of KNIME in terms of working capabilities, in other words, what it is that can be done on KNIME and not on MATLAB in terms of Data Analysis.



MATLAB is one of the  scripting language for data mining and analysis established back in the early 80s.  When it was established, it competed with the likes of SAS and SPSS - also scripting languages.    The GUIs and interfaces for these packages were added much later and generate that scripting language.  The KNIME approach is very different.   KNIME has no scripting language.  What you build and see is what gets executed.     Folks in the forum tell us that KNIME is very easy for a new person to learn, and it is very easy to share with other non-expert users and to deploy in production.    Its also open source and free on the desktop, and that can of course play a huge roll in spreading analytics across an organization.

In terms of functionality, the data manipulation and depth of routines is something KNIME users really appreciate.     But a comparison would be like comparing oceans.  There will always be a method or routine that someone familiar in another package likes and that is why KNIME uses a development approach that allows other packages - such as MATLAB, R and others - to be easily included and used within KNIME when required.

There is a good whitepaper from guys at the Max Plank Institute who use both MATLAB and KNIME available here:    I'll pop them a quick email and ask if they will add something about their experience with both. 

If you KNOW MATLAB well, there will obviously be a learning curve for KNIME.  I am not aware of a MATLAB to KNIME cheat sheet (COMMUNITY!  ARE YOU LISTENING!).

I guess the best way to learn about the difference is to simply install KNIME and go to the Public Server (lower right hand corner of the KNIME interface by default), click on CONNECT, then download a couple of complete examples and play with them.  


Thanks a lot for the reply. I have installed KNIME and have started using it and I am sure it will be a good learning experience!! :)

I'm from MPI-CBG Dresden and I don't have much to add as you got already a very good answer. I personally don't know Matlab but I know R which has a pretty comparable concept. R offers much more functionality and flexibility than KNIME.

BUT: Though Matlab and R code is rather easy to read (compared to real programming languages) they are still a scripting languages.

Compared to R and Matlab,

- KNIME is very easy to learn (even for people who would never touch a programming or scripting language

- KNIME is a visual tool which makes it very easy to build task oriented workflows and it's pretty easy to read them (even if somebody else built it)

In our group, we combined KNIME with Matlab with devloping the Scripting Integration Plugins for KNIME. This enables everybody to do some data analysis without knowing any programming language. If there is the functionality of R or Matlab required we can provide templates which just need to be parametrized by the people. They don't even see the R/Matlab code.

Personally, I like to do my data analysis also with KNIME in combination with R instead of R only, because I like the visual modular workflows. It's easier for me to keep the overview on what has been done.

The only problem is I am not able to connect to the public server no matter how many times I try and hence am not able to download any example workflows from the server.

This is the error being shown:

ERROR RemoteRepositoryView Could not connect to KNIME Server on with user 'guest', reason: connect timed out

How do I fix this?


(Just ran across this old thread so excuse the late reply ... hopefully it helps others.)

If you can't connect to the public server it may be that your corporate firewall is blocking access. Try the zip archive of all public examples. You find the link at the bottom here