KNIME Business Hub Reviews

We use this solution primarily for automation processing, source data, and for data lake or databases. 

I like the visual features and that we can connect using a pixel or an icon for the sources and controls. KNIME is easy to use, it's stable, powerful, and has a lot of features.

For now, the license is quite expensive for us and it would be helpful if that was reduced.

I've been using this solution for a few years. 

The solution is stable. 

We have five people using this solution so we haven't yet tested the scalability. 

We use the community for any questions we have. 

I think the deployment requires a specialist but once it's implemented it doesn't need any maintenance. 

We use the community version; the enterprise version is expensive for us. If we need better support or have other requirements we might need to move to the enterprise version. 

I rate this product nine out of 10. 

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.

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.

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.

The solution allows one to do many things, including data preparation. I was able to apply basic algorithms through just dragging and dropping. This in contrast to Python and other solutions, which involve much coding. 

I would prefer to have more connectivity. The user documentation is insufficient. I would like to see more enterprise level application. There are high end features which should appear, the MLOps platform being one. This feature is key. 

There should be better connectivity to such platforms as AWS and SageMaker, as we rely heavily on AWS in RL. For certain South Asian markets, we plan to go with Azure, so it is important to have connectivity to both of the major clouds.  There should be AI machine learning based algorithms. Such features should be available out of the box with good precision. 

I have worked with KNIME for a couple of months. 

The solution is stable.

KNIME assets are stand alone, as the solution is open source. I have not looked into their enterprise level application costs. While cost is a parameter, I would definitely consider other options which provide value for one's money. 

The solution is good for small scale implementation. Other solutions should be considered for enterprise level implementation. 

I rate KNIME as a five or six out of ten. 

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. 

Knime is used for data analytics.

It can handle an unlimited amount of data, which is the advantage of using Knime.

It already has algorithms included.

I haven't had a lot of time to explore Knime in detail, but when you compare it with Orange, I would like it to be able to find data and collect it from another source. Also, to collect data for Knime from Twitter, Instagram, or Facebook for example, and to add widgets to Knime.

It could input more data acquisitions from other sources and it is difficult to combine with Python. It can be done with special requirements.

I have been using Knime for three months.

In the three months that I have been using Knime, it has been very stable.

From my understanding, it is scalable. It can handle a large amount of data. It indicates that it can handle unlimited amounts of data.

The initial setup was straightforward. It was very easy.

This is an open-source solution that is free to use.

I would recommend Knime to others who are interested in using it.

Students can use Kmine for their research.

I would rate Knime an eight out of ten.

The data analytics capabilities in KNIME are excellent. It's not just a statistical ETL tool. We can go deeper and do various types of tasks beyond straight analytics.

The product is open-source and therefore free to use.

The solution offers lots of different options.

The user interface could be a bit better. It's currently very dated.

They should look at other vendors like Alteryx that are more user friendly and modern. 

From a systems point of view, the tool is not completely user friendly.

Users tell us they would like to do their own analytics and find it difficult to accomplish without the help of a technical service.

You need to be a bit more knowledgeable in order to handle the solution. It's not difficult, it's just more technical than other options.

I've been dealing with the solution for four years.

The solution is very stable. There aren't issues surrounding bugs or glitches. It doesn't crash or freeze. It's quite reliable.

It depends on the requirements you have, however it is scalable, at least for the next two years.

We typically work with enterprise-level organizations. The companies aren't that small.

The technical support is okay. I'd give them three out of five stars.

I don't find any of their online tutorials help anyone at all. I am comparing KNIME with Alteryx mainly due to the fact that those two are the main ETL tools which most of my clients use. The technical support and documentation that are available for Alteryx are quite good. We don't get that level of documentation or videos from KNIME's support. It's very limited. 

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.

The initial setup is not complex. It is pretty easy. However, you have to know what to do. If you have software demo documents or if you have tutorials to support you, then it is easy. I wouldn't say that it's a complex tool at all. It's pretty easy.

The solution is open-source and therefore cheap to use. Anyone can access it. They can just download it off the internet and start. Alteryx is way too expensive. In terms of pricing, it's always better to go with KNIME.

I am both consultant and a vendor right now. We do a bit of consultant work for some of our clients and we give the tutorials to them. We typically get in touch with them, and they send what they need and we do the distribution for them.

I'd recommend new users have their requirements sorted out first so that they know what they need out of the tool. If that is clear, they can install the custom content required in KNIME to get their analytics done correctly. If that is there, then it's a piece of cake.

Overall, I'd rate the solution eight out of ten. If the user interface was better and it offered better technical support, I would rate it higher.