KNIME Reviews

The solution is good for teaching, since there is no need to code. When teaching, the work flow, the process, is easy to explain to students. They understand that there are four steps in data mining on the machine learning project. Data must be injected and cleaned, after which engineering features must be made. Finally, the model must be created and deployed. Both KNIME and RapidMiner have these capabilities.

An improvement which can universally be made to products is to make them more simple. Code-less products are simplified. Both RapidMiner and KNIME should be made easier to use in the field of deep learning. 

While KNIME has all the requisite features, there is a shift from coding to programming with virtual language. It is only a process of making one's solution easier to use. 

I have been using KNIME for more than 14 years. 

The solution is good and they have made improvements over the last version. The same holds true for RapidMiner. Both products are very good. 

The best way to use the solution is to dive in, get practice and use it more. 

I rate KNIME as a nine out of ten. 

We are a solution provider and KNIME is a product that we are working on reselling to our customers. We sell BI tools such as Tableau and many of our customers that are using these tools need to have an AI solution. They have lots of use cases for AI including, for example, those from the financial sector would like to use AI for credit scoring. We also have government clients who will have their own specific use cases.

We have not yet sold it to any of our customers because they are still using the free tools and we are promoting it based on that.

The nicest part of KNIME is that the designer tool is free.

This solution is easy to use and it can be used to create any kind of model.

We are worried about the performance when it comes to using a lot of data that has many rows and columns. On the server-side, we are not sure whether KNIME can manage or handle large amounts of data without issue. It looks like it will easily work for small datasets but we are concerned about performance as the volume increases.

KNIME needs to provide more documentation and training materials, including webinars or online seminars. At this time, it is not sufficient when compared to some other vendors.

The user interface needs to be improved because it looks quite messy and I am not very comfortable using it. 

I have been familiar with KNIME for two or three years but we have been actively interested in it for less than a year.

We have not deployed the entire solution for a customer yet. However, we have been working with the design tool, which does not require deployment. You just have to download it and then it can be used for testing demonstration data.

The price of KNIME is quite reasonable and the designer tool can be used free of charge.

Many of our customers have streaming data and want to use an AI model. We do not yet know whether KNIME will handle live-streaming and it is something that we intend to test.

I would rate this solution a seven out of ten.

Some of the projects that require KNIME are related to sales or the supply chain. We use it to aggregate data from diverse sources rather than predictive analytics. It's primarily for data collection, management, and preparation.

KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data.

We find KNIME useful and convenient for data preparation.

KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too.

My company has been using KNIME for about a year and a half. I don't work on the solution personally, but our analysts do. We use it off and on, depending on the project. It's not every day that we have projects requiring that, but we use it when we do.

KNIME is stable. We haven't seen any issues.

I think KNIME is scalable, but we haven't had a project that would test that sort of thing. The projects requiring KNIME aren't on a huge scale. We haven't tried to scale it, but I think it should be okay. 

My team has used the forum, but we never contacted support for any specific deployment query. I think the online documentation and training are quite sufficient.

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. 

Setting up KNIME isn't hard. When we first installed the solution, it took one or two weeks to understand the various features. After doing it a few times, it didn't take as long. It only takes one or two people to deploy.

The ROI would depend on how KNIME is being used. Some projects would be more economically viable and save a lot of money. Others wouldn't save much.

KNIME could be cheaper, but it's okay compared to other solutions. Our projects are primarily within India, and it is extremely price-sensitive here. If we were doing projects in the UK or the US, it probably wouldn't matter.

I rate KNIME nine out of 10. I would recommend it. I think KNIME is an excellent solution.

I am just considering whether to use it or not. I am trying it to determine whether it is helpful or not. So far, it can solve my data analysis problems and I think it's a powerful data analysis tool.

It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop.

They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning.

The stability is great.

Most of the time it can solve the problems.

I have not used KNIME for a very long time so I have not used technical support so far.

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 think the setup is straightforward.

I would rate it at nine out of 10. It's good, it makes thing easier.

I use KNIME for clustering data analysis. 

It's a coding-less opportunity to use AI. This is the major value for me.

I had some difficulty connecting to servers. It asked me to set something up on my server and it asked me for a code that I needed to generate on the server. There were several steps that I messed up. I followed all of the instructions but I couldn't manage it at all. I followed the directions in several forums to find out the problem.  

There should be better documentation and the steps should be easier. 

I have been using KNIME for three to four months. 

I haven't needed to contact their support. 

I tried Python and Microsoft. 

The initial setup was super easy. It was really quick. I did it myself for personal use. It didn't take longer than half an hour. 

Some of the samples are outdated but my advice to someone considering KNIME is to use their samples. 

I would rate KNIME an eight out of ten. 

In the next release, the should have more comprehensive samples.

Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing.

Lot of manual work has been automated through this and single solution created on this can be used by others, too. We have implemented the same thing in our organization as CAE.

Data handling capacity. Currently it handless 25M rows of data, after which you will face lagging issue.

System resource usage. Knime will occupy total system RAM size and other applications will hang.

I have been using it for 18 months.

Nope.

When the data limit exceeds, it will get lag.

A nine out of 10.

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

It is easy to setup.

It is free of cost. It is GNU licensed.

No.

It is best one for harmonizing data with no cost included.

I've been using some of the analytics and photo manipulation features. I'm a teacher, and I've been using KNIME in my university.

It's a huge tool with machine learning features as well.

There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger.

I've been using this solution for two and a half years.

Overall. it's stable. However, every time there is a major version release, we end up having to upload many of the nodes again. It takes some time to do the version change.

It is scalable, especially with a server.

The technical support is excellent, fast, accurate, and friendly.

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

The initial setup is easy.

You should do the KNIME courses, particularly the first two courses.
They would give you a very good base to make KNIME work nicely, and you would also know how it really works.

It is a really good system, and on a scale from one to ten, I would rate it at ten.

It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript. 

It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved.

The scalability needs to be improved as well.

It's more or less stable.

It is scalable to a certain extent.

It is fairly easy to setup KNIME.

The client versions are mostly free, and we pay only for the KNIME server version.

It's not a cheap solution.

For experimental work, KNIME is a good solution. However, for special task oriented developments, it's not the best.

Considering this, I would rate KNIME at seven on a scale from one to ten.