KNIME Reviews

We use KNIME for analyzing data, for ETLs, and analyzing for machine learning.

KNIME is easy to learn. You can code with KNIME using the visual coding platform if you know how to code. If you're working in an account management or financial department, you can use KNIME to work with a huge amount of data quickly. You can use KNIME to schedule your workflows, send emails, and write codes.

The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data.

I have been using KNIME for eight years.

KNIME is a stable solution. In the previous version, sometimes KNIME would get stuck, and we had to restart the server too many times. Sometimes, we faced a lack of memory issues with the solution.

I rate KNIME an eight out of ten for stability.

Less than ten users are using KNIME in our organization.

I rate KNIME an eight out of ten for scalability.

KNIME’s technical support team responds quickly. You can write your problems in the solution's forum, and they will answer you.

KNIME's initial setup is not easy and needs someone who knows Linux to do it.

A Linux engineer can deploy KNIME quickly, whereas someone who doesn't know Linux will take longer.

There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server.

KNIME is a perfect solution for small and big companies, especially people who are using Excel. KNIME is very easy to learn and implement, and doctors and lab personnel can use it. Lots of companies are supporting KNIME and writing their own extensions. Data analysts and data scientists are using the solution for ETI processes.

Overall, I rate KNIME an eight out of ten.

We use KNIME for tax technology. We want to implement technology in our tax domain.

KNIME is very fast and scalable. There are a lot of connectors available in KNIME.

KNIME is less secure than Alteryx. KNIME's documentation is not strong. I cannot make good documentation on a KNIME workflow like in Alteryx. Alteryx has more color options where I can put tools into different containers and write some annotations. I felt that was missing in KNIME.

I have worked with KNIME for one year.

KNIME is a stable solution. However, you have to be mindful while working with any open software because it's open to anything.

KNIME is very easy to scale because it's an open source solution. There are a lot of professionals who continuously put some effort into introducing scripts because it is easy to integrate with other technologies. So the add-ons are easily available for KNIME.

KNIME's customer support is good. In three and a half years, I found solutions to 99% of my questions.

Positive

KNIME's installation is very easy. All you have to do is log on to the website, check for the latest version, and hit the download button to get it.

KNIME's deployment takes around five to ten minutes. Maintaining the designer version of KNIME is more or less the same as maintaining Alteryx.

KNIME is a cost-effective solution because it’s free of cost.

Small, medium, or enterprise businesses can use KNIME. You have to be more careful in downloading because it is an open-source solution, and anybody can even spread a virus. It's up to the users whether they want to take that risk. But I don't see such problems working with the Alteryx community, where all the information is much safe to download and upload.

I would suggest KNIME to someone with a low budget looking for a cost-effective solution. However, I would also give a disclaimer that they should be careful while downloading the connectors from the KNIME community because it's more open. Since it is an open-source solution, there are high chances of having some security issues.

Overall, I rate KNIME seven out of ten.

I'm a professor at the local university. So, I used it to train virtual students in mechanical engineering.

I'm training a class for mechanical engineers on factory utilization and the basics of data science. That's what I use it for.

It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME.

In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. 

Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them.

I have been using it for four years. 

I've never had any problems with it, so it's a ten out of ten.

I would rate the scalability a nine out of ten. For a basic training course, it's still fine. But I'm not a professional in using KNIME.

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.

Overall, it's still easier than using Python, so it's still fine. But, actually, they made it more complex by switching from the last version to the one before.

We're using the free academic license just locally. I went for KNIME because they have a free academic license. And to be honest, I never bothered to check the prices.

I like it a lot. I would advise that you shouldn't be afraid of data science. It's actually straightforward.

Overall, I would rate the solution a nine out of ten. 

It's for big data or descriptive analytics involving data manipulation, formatting, and formulas.

Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time.

It's like an Excel on drugs. It's more powerful than Excel, and it allows me to do macros easily.

I downloaded KNIME myself, and it's for self-learning. It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge.

I've been using this solution for about three years. I last used it in my previous company about two months ago. We are not using it in my current company, but I'm using it for self-learning.

It's stable. I'd rate it a nine out of ten in terms of stability because when I load huge data, it sometimes takes a while and crashes. If I don't load it much, it works fine, but if I overload it, it crashes.

It seems scalable.

It involved just downloading the app from the web. I didn't have any interaction with them. I just downloaded the free version.

They have different versions, but I am using the open-source one.

I'd recommend it, but it comes with a trade-off that you need to spend a lot of time on your own to understand how it works. It's user-friendly, but the fact is that I downloaded it by myself, so I didn't have any formal support on how to use it. It was used in my previous company. They had the license and they encouraged us to use it. That's how I know it.

I'd rate it an eight out of ten because I am not able to do some of the things, which could be because of my lack of knowledge, but it's a very good product. I see the benefit in terms of efficiency.

We are using KNIME for price prediction, privacy missions, the commander model, ETL, and a couple of algorithms we've developed.

One of the greatest advantages of KNIME is that it can be used by those without any coding experience. Even those with no coding background can use it. 

KNIME can be used by people without coding experience. It can be used by people who don't have an IT background and don't have coding knowledge. This is different from Python or R, which require coding experience to use.

When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area.

I have been using KNIME for approximately one month.

I'm not sure if it is stable, we'll have to see how KNIME performs with larger amounts of data, as I have heard it is not very reliable. With smaller data sets, however, it seems to be stable.

We will use this solution more in the future when we do not need people with coding experience.

We have two people who are using this solution in my organization.

I have not used the support from KNIME.

I used the open-source package and started experimenting with it in Python, R, and KNIME. For KNIME, I had to go through the KNIME forum for troubleshooting. I didn't get a response for any of the issues I encountered on the KNIME forum. As for other open-source languages, I haven't received a response for any of the issues I faced either.

The initial setup of KNIME is easy. It can be done with the interface within half an hour.

I had taken some online courses and read about KNIME, and I wanted to try out a drag-and-drop software. I was interested in evaluating KNIME, and this is why I am using it.

My advice to those who are new to data science and don't have any coding experience would be to use KNIME, along with some other programming languages. KNIME is great for creating visualizations and dashboards, and I have advised a few of my colleagues to use it for their own projects.

I rate KNIME a seven out of ten.

We use the solution for data analytics and logic design.

The product is working fine with Oracle.

It is is written in Java. If they can output the Javascript, it will be much better. Also, it could be integrated with Visual Studio.

I have been using KNIME for three years.

20 users are using this solution. Scalability is quite easy, but handling many notes can become messy.

Most of the things is available in the community.

It's quite easy to setup.

I have a CSV reader. When I reset that CS reader, and It gave some error.

I have a CSV reader, and I encounter an error whenever I try to save. However, if I reset the CSV reader, I am able to save successfully. It’s a rare issue, but there's something wrong with the CSV reader. The error message doesn't provide a solution, only indicating a problem with the CSV reader.

I want to save the project but always face saving issues. If I reset the node, the saving works fine. The error message isn’t clear about what is wrong or how to fix it. I discovered on my own that resetting the CSV reader from green to yellow allows me to save the project. This issue is quite rare.

Last Friday, there was a widespread CrowdStrike issue, and I had to restart my computer. After restarting, I lost my entire project.

I recommend the solution.

Overall, I rate the solution a nine out of ten.

I use KNIME to simplify the modeling process. 

The tool's analytic capabilities are good. 

I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial.

The solution is scalable. 

I haven't contacted the tool's support yet. 

The tool's deployment is easy. 

I use the tool's free version. 

It takes some time to get familiar with it. I'm not sure how long it will take in the meantime. If one person learns it but the whole institution doesn't use it, that's a problem. Some people in our department use QuickSight, I use Tableau. We speak different languages, and it's hard for us to work together. Some use KNIME. We use it and then stop. We switched to Tableau, but it's expensive, so they're trying QuickSight. I don't know which platform we'll end up using.

We're still exploring KNIME for data manipulation, though Tableau or Power BI might be more convenient. I've used Alteryx before, and KNIME seems similar. I mainly use KNIME for machine learning, not as much for data manipulation.

I rate the overall product a seven out of ten.

I'm a professor, and I learned about KNIME from a data science course. I use KNIME for data visualization, manipulation, and generation.

What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node.

It's also helpful to learn more about the different concepts in KNIME, such as data mining, neural networks, and other visualization nodes for generation. You can gain a lot of insight from the tool as a data scientist.

Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing. This is an area for improvement because not all nodes appear in the 64-bit system. In other systems, you get to use all nodes or features. It should be uniform in all systems, though I have no idea if it's a software problem or a corruption in the system that's in the college lab. At home, I can see and access the image reader node, but in school, that node is missing.

What I want to be added to KNIME is the feature of extracting data from social media platforms, whether structured or unstructured and for that data to be automatically converted into a CSV file that I can use. I want a data cleaning and collection process from KNIME that works for social media platforms because datasets in social media can serve as business intelligence or can aid businesses. Social media is the trend nowadays, so I want a KNIME node to analyze data from social media platforms.

I'd been using KNIME for three months now.

In my three months of using KNIME, its stability has been okay, but I want to explore the tool more. Stability-wise, it's a seven out of ten. When the network is stable, then KNIME is okay to use.

KNIME is a scalable product, so I'm rating it as nine in terms of scalability.

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

KNIME was easy to set up, so it's a ten out of ten, setup-wise.

KNIME is an open-source tool, so it's free to use.

At the moment, only ten students use KNIME. The course just started.

In my three months of experience with KNIME, it's an eight out of ten.