Try our new research platform with insights from 80,000+ expert users
NagendraVuppala - PeerSpot reviewer
Tax Manager at RSM
Real User
Top 5Leaderboard
A fast, cost-effective, and scalable solution, but its documentation is not strong
Pros and Cons
  • "There are a lot of connectors available in KNIME."
  • "KNIME's documentation is not strong."

What is our primary use case?

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

What is most valuable?

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

What needs improvement?

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.

For how long have I used the solution?

I have worked with KNIME for one year.

Buyer's Guide
KNIME
March 2025
Learn what your peers think about KNIME. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,767 professionals have used our research since 2012.

What do I think about the stability of the solution?

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

What do I think about the scalability of the solution?

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.

How are customer service and support?

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

How would you rate customer service and support?

Positive

How was the initial setup?

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.

What about the implementation team?

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

What's my experience with pricing, setup cost, and licensing?

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

What other advice do I have?

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.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
AltanAtabarut - PeerSpot reviewer
Solution Consulting, Growth, Analytics at Akinon
Real User
Top 5Leaderboard
A no-code platform that can be used for a lot of predictive modeling
Pros and Cons
  • "Since KNIME is a no-code platform, it is easy to work with."
  • "KNIME is not good at visualization."

What is our primary use case?

We use KNIME for a lot of predictive modeling. We use it to grab data, prepare it for modeling, do automated machine learning analysis, sometimes forecasting, and then try to deploy the models into production.

What is most valuable?

Since KNIME is a no-code platform, it is easy to work with. You don't have to write any codes and try to fix all the bits and pieces of coding or the intricacies of the programming language. Instead, getting a quick data prep or big data and eventually running it through your hypothesis is pretty fast. It's not ideal for huge data sets worth gigabytes, but it's okay since very few people have big data sets.

What needs improvement?

KNIME is not good at visualization. I would like to see NLQ (Natural language query) and automated visualizations added to KNIME.

For how long have I used the solution?

I have been using KNIME for two to three years.

What do I think about the stability of the solution?

Unless you are working with terabytes worth of data, KNIME is a stable solution.

What do I think about the scalability of the solution?

The solution is scalable and can be used up to terabytes of data. Around two to three people are using the solution in our organization.

How was the initial setup?

The solution’s initial setup is quick and easy.

What about the implementation team?

One person can deploy the solution within ten minutes.

What other advice do I have?

The solution is very essential when we require an explainable data modeling pipeline. We can show the workflows of KNIME to our customers and talk about it instead of showing the code and expecting them to read, which they can never do.

The process of providing KNIME to the client, how it works, where we get the data, what the initial data statistics were, and what we get in return are pretty explainable. We worked on multiple retail projects and insurance scoring projects.

KNIME is perfect for data pre-processing projects. The important thing is that when someone builds a KNIME workflow, we can quickly onboard and change it for something else. It means that we don't need to read and understand the code. It means that it's replicable and reusable.

If somebody does something, somebody else can quickly onboard and enhance, improve, or totally change the workflow from scratch. It's pretty hard and time-consuming for typical use cases where we utilize coding. KNIME's open-source nature has a good impact on our analytics work.

Recently, KNIME added something relevant to generative AI integration, which was a good move. Alteryx is slightly more powerful than KNIME, and Dataiku is more powerful than both KNIME and Alteryx. I sometimes work with the on-premises version of KNIME and sometimes the cloud version. The solution does not need any maintenance.

Users should quickly start using KNIME for whatever they want to do, and they'll learn it on the go easily. I would recommend the solution to other users.

Overall, I rate the solution an eight out of ten.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
Buyer's Guide
KNIME
March 2025
Learn what your peers think about KNIME. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,767 professionals have used our research since 2012.
reviewer2382516 - PeerSpot reviewer
Student at a performing arts with 201-500 employees
Real User
Simplifies data modeling but needs to add longer training videos
Pros and Cons
  • "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."

What is our primary use case?

I use KNIME to simplify the modeling process. 

What is most valuable?

The tool's analytic capabilities are good. 

What needs improvement?

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.

What do I think about the scalability of the solution?

The solution is scalable. 

How are customer service and support?

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

How was the initial setup?

The tool's deployment is easy. 

What's my experience with pricing, setup cost, and licensing?

I use the tool's free version. 

What other advice do I have?

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.

Which deployment model are you using for this solution?

On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
Student at ISCTE - INSTITUTO UNIVERSITÁRIO DE LISBOA
Real User
Top 20
Intuitive design and helps with academic work while graphic features need clarity
Pros and Cons
  • "KNIME is more intuitive and easier to use, which is the principal advantage."
  • "KNIME is more intuitive and easier to use, which is the principal advantage."
  • "For graphics, the interface is a little confusing."
  • "For graphics, the interface is a little confusing. So, this is a point that could be improved."

What is our primary use case?

I use KNIME for my academic works.

What is most valuable?

KNIME is more intuitive and easier to use, which is the principal advantage.

What needs improvement?

For graphics, the interface is a little confusing. So, this is a point that could be improved.

For how long have I used the solution?

I have been using KNIME for six months.

What other advice do I have?

I'd rate the solution seven out of ten.

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Other
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Flag as inappropriate
PeerSpot user
Yasin Sarı - PeerSpot reviewer
Senior Data Analyst at a comms service provider with 1,001-5,000 employees
Real User
Top 5Leaderboard
An easy-to-learn solution that can be used for analyzing data and machine learning
Pros and Cons
  • "KNIME is easy to learn."
  • "The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."

What is our primary use case?

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

What is most valuable?

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.

What needs improvement?

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

For how long have I used the solution?

I have been using KNIME for eight years.

What do I think about the stability of the solution?

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.

What do I think about the scalability of the solution?

Less than ten users are using KNIME in our organization.

I rate KNIME an eight out of ten for scalability.

How are customer service and support?

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

How was the initial setup?

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

What about the implementation team?

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

What's my experience with pricing, setup cost, and licensing?

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

What other advice do I have?

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.

Which deployment model are you using for this solution?

On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
PeerSpot user
Data Analytics Consultant at Optivia
Real User
Good workflow tools, supports Python and R integration
Pros and Cons
  • "The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
  • "I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."

What is our primary use case?

This solution is primarily used for various data analytics in an enterprise environment. 

The reality of any data analytics project including Data Science is that 90% of the effort goes into data sourcing and preparation. Data usually comes from multiple sources including data warehouses, web scraping, Excel input, free text, etc. KNIME allows you to do the 90% plus other predictive functionality.

How has it helped my organization?

It is a free open-source tool that performs very similarly to other expensive tools. KNIME has been great for me over the years. It allows me to connect to various sources including data warehouses, then put the processing logic together (ETL-like), which can be quite complex and produce the required output. Ultimately, it would go into Excel or Tableau for presentation.

What is most valuable?

The features that I find most valuable are:

  1. The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes.
  2. Unlimited volume of data; you are only limited by the machine you run on.
  3. Python and R integration.
  4. Predictive functionality and text analytics. If it is not enough then you can use custom Python and R scripts.
  5. Looping functionality.
  6. Variables allow you to parameterize your flows.
  7. Run one node at a time, which is something that Alteryx users dream of doing.
  8. Managing (collapsing) sub-flows, which is another thing that Alteryx container users also dream of.

What needs improvement?

The areas that I feel need improvement are:

  • It needs support for a joiner node to have three outputs (left unmatched, matched, right unmatched), as competitors do (have not checked 2019/20 releases).
  • I need the ability to add additional comparison conditions to a join. For example, in SQL you can specify only rows with a date fitting within a date range from the joined file. At the moment in KNIME, you should allow a join explosion to take place and filter what you need later, but sometimes the output becomes too big.
  • It would be helpful to have more examples of Java code for nodes, like Java Snippet.
  • I would like to have this solution show row counts on canvas, as it would improve the control and speed to build the workflow.
  • The pseudo-code types could be rationalised into one (e.g. only Java).
  • I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script.

For how long have I used the solution?

I have been using KNIME for between four and five years.

What do I think about the stability of the solution?

My system occasionally may crash like other similar tools, although autosave is available.

What do I think about the scalability of the solution?

Scalability is limited to a desktop application.

How are customer service and technical support?

Obviously, as an open-source application, your options are limited but I have found answers on forums when I needed help.

Which solution did I use previously and why did I switch?

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.

How was the initial setup?

It is a relatively simple install. You can even avoid installing it and run from a directory.

What's my experience with pricing, setup cost, and licensing?

KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website. The fact that KNIME is open source may create challenges from an IT security view in an enterprise environment.

Which other solutions did I evaluate?

For this review, I would include Alteryx and Lavastorm (the latter is no longer available).

What other advice do I have?

If you need a good Visualisation functionality, you should use Tableau or something of that caliber. However, the data prep can be done KNIME, which would give you extra confidence that what goes into your Visualisation layer is correct.

Overall, KNIME is definitely worth considering.

Which deployment model are you using for this solution?

On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
reviewer2332260 - PeerSpot reviewer
Professor of Digital Production at a educational organization with 1,001-5,000 employees
Real User
Top 20
Stable, pretty straightforward to understand and offers drag-and-drop functionality
Pros and Cons
  • "I've never had any problems with stability."
  • "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."

What is our primary use case?

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.

What is most valuable?

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.

What needs improvement?

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.

For how long have I used the solution?

I have been using it for four years. 

What do I think about the stability of the solution?

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

What do I think about the scalability of the solution?

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.

Which solution did I use previously and why did I switch?

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.

How was the initial setup?

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.

What's my experience with pricing, setup cost, and licensing?

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.

What other advice do I have?

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. 

Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
Professor at Mines Rabat
Real User
Top 20
An excellent choice for users seeking a powerful and flexible platform for data analytics and machine learning offering user-friendly visual interface, extensive library of plugins, and robust support
Pros and Cons
  • "The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
  • "To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."

What is our primary use case?

As a university professor instructing courses on data mining and machine learning, I incorporate both KNIME and another software application into my teaching. This approach allows me to demonstrate various use cases effectively. I actively engage my students by having them utilize both software applications, providing practical hands-on experience in the areas of data mining and machine learning.

What is most valuable?

The most valuable is the ability to seamlessly connect operators without the need for extensive programming.

What needs improvement?

To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages.

For how long have I used the solution?

I have been using it for more than ten years.

What do I think about the stability of the solution?

I would rate its stability capabilities nine out of ten.

What do I think about the scalability of the solution?

It provides good scalability abilities, I would rate it eight out of ten. Currently, more than sixty individuals use it on a daily basis.

How are customer service and support?

They are helpful and I am highly satisfied with their customer support services. I would rate it nine out of ten.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We use Orange as well.

How was the initial setup?

The initial setup is straightforward.

What's my experience with pricing, setup cost, and licensing?

While there are certain limitations in functionality, you can still utilize it efficiently free of charge.

What other advice do I have?

I would recommend it, especially for those who prefer not to program or have limited coding intervention. Overall, I would rate it nine out of ten.

Which deployment model are you using for this solution?

On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user