KNIME vs SAS and Alteryx

Dear users,

My company is now in a tool research project analyzing the features of KNIME/SAS/Alteryx for Marketing purposes. 

We are now using SPSS Statistics but want to move to a more robust and user friendly tool which makes portability of projects to other employees easier, requires less manual coding and easier to work with. 

From the tools we have seen KNIME seems the best fit but because it is open source the IT staff is a bit reluctant to implement as the support might be less than they are used to. 

What are your experiences with KNIME

  1. in terms of features in comparison with other tools e.g. SAS/SPSS/Rapidminer?;
  2. in terms of support;
  3. in terms of features, is it easy to get used to for example;
  4. what are your biggest pros with KNIME?;
  5. what are really turnoffs with KNIME?

Hope you can help me out with this as we are 'lost'.



Hi Rishi,

I will leave the experiences part to our users, as I am part of the company behind the KNIME Analytics Platforms, the

About your support question: We at offer professional support for all of our commerical products as well as for the KNIME Analytics Platform. If you want to know more about this, could you send us an EMail to our sales address (

We are happy to get you started and answer your questions.

Best regards, Iris

Hi Rishi,

  1. As KNIME integrates R and Weka (and even RapidMiner), there is generally no functionality gap to be feared in comparison with other tools. Some things are more convenient elsewhere, but you can tie in special-purpose convenience stuff fairly easily.
  2. Commercial support can be procured at reasonable rates, and while the folks may sometimes have some capacity problem or another, I have seen and heard enough from large companies charging millions of USD/EUR a year and still failing to support/resolve "that one issue" you may have. The implementation experts are easy to reach at KNIME, and your contribution truly counts compared to industry behemoths. Also bear in mind that KNIME is first and foremost of all a tool to empower analytics power users on local machines, and only if you grow into collaboration needs with a server setup it becomes inevitable to have IT support to back you up. And as servers comes with good setup support I personally don't see the problem (judged from two large companies who successfully implemented it at my request thanks to KNIME's affordability). This affordability is a serious business case to be made to management, which IT cannot very easily undermine in the long run, even if KNIME is slightly "different" from the rest of the pack. Gartner Magic Quadrant leadership for Advanced Analytics should ring in IT circles!
  3. Best ever, to my mind. It has its quirks of course, but so do mutli-million dollar packages - which often don't get fixed/updated at all for a long while.
  4. Extensibility and ease of use, no doubt.
  5. From an analyst perspective hardly any, except when you accidentally max out your machine again and KNIME struggles to stay alive... :-) Other than the occasional stack/heap space/freeze issue owed to this I'm not too worried. It's table-centric and could use some more dashboarding capabilities for sure, but these are inbound with the increased exploitation and layout convenience of the JavaScript views.

HTH. :)



For marketing area this case study from Rosaria might be interesting to you. Not sure what are your typical use cases, though that teaser also presents integration with BIRT, so reporting can also be covered with KNIME.

Hi Rishi,

Take a look in my comments below related with my personal experience:

I have been using Knime since the beginning of 2016 and so far, it is a kind of open source Alteryx.

I think that Knime is growing fast because users keep pushing/helping development and new implementations.

The forum/community works pretty well and the platform is easy to use although I still think that there is space to reduce the learning curve anyway.

There are so many nodes that I can't tell you wich one can help you most but if you like you can also right your own codes in R/Python/Java (not my case). In my personal perspective, they should introduce econometrics nodes (in some cases I need to use Gretl).

I started to study Machine Learning after learn Knime because its so easy, useful and powerful.

I can't find a tool with better cost/benefit.



We are a finanical firm with global offices, but a small IT team. Having applications with minimal support is key. KNIME fits that without problems.

We started with Alteryx about two years ago. We discovered KNIME through academic literature and tested it. We took a quick look at PowerBI, Pentaho and RapidMiner also. After that it was a quick switch to KNIME, and an equally quick move to the server version. We now run KNIME within a small team, with IT support solely to maintain thge virtual machine the KNIME server runs on. We are close to considering the web portal license to extend its use. 

We use KNIME and connect to SQL Server, Oracle, Neo4j for databases. We connect to Bloomberg for live data feeds, to the web using Selenium and Palladium nodes, and to Tableau for visualisation. Analytics is done natively, and using python. We have used it as the backbone for text analysis, data analysis, image analysis, and web analysis. File system and system control is done via natively through the knime nodes and with java through the snippets. We are not java programmers but it is easy to pick up enough to work. Job scheduling is controlled by the KNIME server, and job monitoring is done by a KNIME flow coupled into Tableau. 

We have no problems with the desktop Analytic Platform. It did take a little work to get the KNIME server installation going, especially compared with Confluence or Tableau which fully installed themselves. We are a Windows shop and the Server installation for Windows is not automated. However, Iris and the KNIME team was very helpful in guiding us, and once started it just runs. I have no doubt they will be very helpful.

We have not needed any support from IT beyond hardware and some initial database driver setup, largely to find jdbc drivers. Connection with python was straightforward once we got python properly installed. The fact it is an open source has not been a problem. Updates are straightforward, we have been through major and minor version updates. We manage them ourselves, and not by the IT team.

Our Server workflows are on network drives and are automatically covered by global backup policies, as are our individual workflows. We have a disaster recovery policy which probably needs reviewing as we have upgraded from the time it was put in place. From an IT support perspetive, our IT team never need to do anything with it. 

I'm sure you have tested out KNIME's analytic abilities and ETL power. My tuppence's worth is KNIME doesn't try to be the best, it becomes the best by allowing you to integrate with something that actually is the best for the task at hand. Being open source makes this possible. It's an integration tool. The others try to be the best by themselves, and fall far behind. Open source is what makes this possible.

My vote, go for KNIME, forget the others. Your IT team will worry they don't have a job!







I work in an advanced analytics group. We use and have made significant investments in Alteryx. Within that group I am probably the sole user of KNIME. Having spent a bit of time with both platforms I think the first thing you should consider is whether you are going to use the geospatial capabilities in Alteryx and license the data sets (e.g. Experian, Dunn & Bradstreet, CASS, TomTom). If geospatial is important there isn’t a more user friendly option than Alteryx. Creating trade areas with their related demographics is trivial in Alteryx, and I’m not aware of another system that enables that functionality so easily.

If you aren’t going to use the geospatial tools and data I’d suggest KNIME. The integration with R is better and overall it seems to be more flexible than Alteryx

Dear KNIME gurus,

Thank you for your replies. I really appreciate this as the process of choosing one tool over another is quite a hassle especially if one of these tools is open source and employees are used to their working method for years and fear changes.

I will discuss your input with them and take into consideration during this project.

Best Regards,



This shared spreadsheet might be useful to you all. It translates Alteryx Tools to Knime nodes (and vice versa when complete)… It is a work in progress so please do contribute to updating if you can.