KNIME Reviews

Our analysts use Knime in the company for data modeling, data wrangling, and data preparation. We have a good amount of data that we work with.

I do not personally use the product, but I am familiar with its usage through my analysts.

Data preparation and data modeling are easy to do.

It is very fast to develop solutions.

There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool. This would make workflow development faster because several tools could be used together, based on the function that is chosen. Each would complete one of the constituents of the task.

We have been working with Knime for approximately one year.

This product is quite stable and we haven't had any problems.

Knime is a scalable solution and we haven't experienced any issues. There are six of us who are using it.

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

The initial setup is easy.

The price for Knime is okay.

I would rate this solution a nine out of ten.

We have used KNIME for text processing, specifically for leveraging the text processing features for entity extraction, document classification, relationship extraction, and other such NLP tasks.

We are far from reaping the benefits of this platform as an organization. However, so far, we have been able to appreciate the considerable reduction in prototyping time.

The most useful features are the readily available extensions that speed up the work. For instance, KNIME offers multiple document taggers, which one can use with relative ease. Similarly, the number of predefined NER taggers are also very handy.

The documentation needs a proper rework. 

I primarily use this product for data engineering and data wrangling.

The most valuable feature is the data wrangling, which is what I mainly use it for.

From the point of view of the interface, they can do a little bit better.

I have been using KNIME for three years.

Scalability is not a relevant consideration for KNIME because I am using it myself.

I feel that the community is a bit too Java-oriented. It would be better if it grew and became more diversified, from a data engineering perspective.

The initial setup is straightforward.

There are different licenses available.

The only other option I have is Alteryx and the functions in KNIME are better.

This is a very handy tool and I use it quite interactively. I am not an expert-level user and it pretty much has everything that I need.

I would rate this solution an eight out of ten.

• It has an excellent interface
• Is very easy to use
• It really boosts productivity
• The performance is impressive, even in a normal laptop
• The diversity of tools for pre-processing is very handy
• The integration with R and Weka, make it the perfect Data Mining solution

We have use it in industry projects, for internal experiments, and for teaching.

The diversity of native algorithms could be improved.

I have been using this solution for the past three years and it is an excellent solution.

No issues with deployment.

No issues with stability.

No issues with scalability.

Once I had to contact the customer service, and it worked quite well.

Knime has a considerable support community, so there are few problems that you can not find in the documents of the community.

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.

The setup is straightforward, just download and start using.

I implemented in-house and for other companies.

Very high, since it has low costs and it is very easy to use.

Yes, but long ago. I evaluated Oracle Data Mining, Clementine, and SAS Enterprise Miner.