I used SAS which is good for data wrangling because it displays most of the end results with one simple code. 

Compared to RapidMiner, at the moment I would go for KNIME, but that's largely because I haven't used RapidMiner much for the last year. It may have improved enormously since then. It was a very good package. They do much the same thing.

I'm more familiar with KNIME, so I would be able to talk more about it, whereas for RapidMiner, I was very enthusiastic when I used it. KNIME is a bit cheaper in a sense.

In RapidMiner, you can have up to 10,000 rows of data free of charge. For many things that I do, 10,000 rows of data is enough. I use quite a few UK government surveys, and I get the raw data from the UK Data Archive. They're often of the order of 10,000, 8,000. So, under 10,000 rows. I could use it free of charge.

I used RapidMiner. I have not been using it in six years. I used to use it six years ago. Then I switched to KNIME because a lot of my colleagues are using KNIME, so it felt like the right way to do it.  

Moreover, I switched from one university to another, and at my new university, other colleagues are using KNIME as well. So, for the students, it's easier to go just with one product.

We use Orange as well.

I have experience with Excel, and I faced some limitations since my company had loads of data to analyze. Considering that my company had loads of data to analyze, I would say I find KNIME to be very useful.

We used Alteryx prior to KNIME.

I've not used any other tool besides KNIME, but I'm planning to try RapidMiner, which I've not yet installed.

We used Rapidminer earlier. We switched to KNIME as it is a better tool for data mining.

Recently I have been using Alteryx so I have collected a few points on differences in both tools. Both are good, I can conclusively say I could go back to KNIME and be as effective data professional as I am with Alteryx.

I have to use Alteryx due to my client's tool choice, but I know that what I am doing with Alteryx right now could be done better in KNIME. Of course, Alteryx has its own advantages for certain areas.

I have used Alteryx. I prefer this solution over Alteryx because of the pricing point. KNIME is free and open source. 

I have used Python. The logic is the same, but the interface is totally different.

I have not used other solutions other than KNIME.

I had been using a combination of Excel macros and manual entry. I switched because I was looking for something a bit quicker and automated, something to remove as much human error as possible.

I used Power BI, but when I found KNIME, there was no going back.

I wrote Python in different IDE, however KNIME is easier to tackle with changes in data sources, processes, and expectations, etc. It is simple to work around with different situations for testing and comparison. 

Before KNIME, I used SQL language and Excel for data analysis but machine learning algorithms. In parallel to KNIME, I worked on a few projects with R and Python separately. So I cannot say that I switched from different solutions.

But just for ETL with Excel, KNIME brings me better visualization, rich function set, preserving operations to repeat again and better performance on the same hardware.

We worked with Alteryx, but we switched to KNIME because that's what our customers wanted. Alteryx is a good solution, but the cost was exorbitant for the client. 

We also use Alteryx. We use both solutions, depending on the client. I tend to recommend Alteryx. For someone who has good technical knowledge, they can go with KNIME. However, if they're not a techy person, I would recommend Alteryx for them.

Previously I used some programming tools, but I needed to do a lot of coding. KNIME is simpler to use.

The most important factor when I'm looking at which vendor or product to go with is the program's features.

I created my own script. I switched to KNIME because it simplifies the flow of my script into one workspace, and doesn't necessitate a lot of jobs in my system.

Alteryx. KNIME is much cheaper. The KNIME desktop client is free. KNIME handles 95% of our requirements.

I tried Python and Microsoft. 

Prior to Knime, we were using Alteryx. However, Alteryx is too costly and our customers don't want to pay for it.

Previously, I was using SPSS Statistics, although that was ten years ago. I had a gap in data mining and the statistic field as a whole.

Previously, we used Alteryx for harmonizing. Cost was the main reason for the switch.

I used the old Clementine solution (now in the IBM portfolio). I also keep using Weka, but now I tend to use Knime more, which ends up being more versatile, since it can integrate R and Weka.