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Vivek Rane
CEO at Alpha Analytics
Real User
Top 20
Easy to use, with good data wrangling and preparation capabilities
Pros and Cons
  • "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."

What is our primary use case?

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.

What is most valuable?

Data preparation and data modeling are easy to do.

It is very fast to develop solutions.

What needs improvement?

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.

For how long have I used the solution?

We have been working with Knime for approximately one year.

What do I think about the stability of the solution?

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

What do I think about the scalability of the solution?

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

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

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

How was the initial setup?

The initial setup is easy.

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

The price for Knime is okay.

What other advice do I have?

I would rate this solution a nine out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: partner
Solutions Architect at a retailer with 10,001+ employees
Real User
Should have better connectivity, although the solution is stable and allows for easy dragging and dropping of basic algorithms
Pros and Cons
  • "I was able to apply basic algorithms through just dragging and dropping."
  • "I would prefer to have more connectivity."

What is most valuable?

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. 

What needs improvement?

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. 

For how long have I used the solution?

I have worked with KNIME for a couple of months. 

What do I think about the stability of the solution?

The solution is stable.

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

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. 

What other advice do I have?

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. 

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Trainer at a government with 10,001+ employees
Real User
Free to use, stable, and easy to install
Pros and Cons
  • "It can handle an unlimited amount of data, which is the advantage of using Knime."
  • "It could input more data acquisitions from other sources and it is difficult to combine with Python."

What is our primary use case?

Knime is used for data analytics.

What is most valuable?

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

It already has algorithms included.

What needs improvement?

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.

For how long have I used the solution?

I have been using Knime for three months.

What do I think about the stability of the solution?

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

What do I think about the scalability of the solution?

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

How was the initial setup?

The initial setup was straightforward. It was very easy.

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

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

What other advice do I have?

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.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
Teacher at a university with 1,001-5,000 employees
Real User
Coding-less opportunity to use AI and it is easy to set up
Pros and Cons
  • "It's a coding-less opportunity to use AI. This is the major value for me."
  • "There should be better documentation and the steps should be easier."

What is our primary use case?

I use KNIME for clustering data analysis. 

What is most valuable?

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

What needs improvement?

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. 

For how long have I used the solution?

I have been using KNIME for three to four months. 

How are customer service and technical support?

I haven't needed to contact their support. 

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

I tried Python and Microsoft. 

How was the initial setup?

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. 

What other advice do I have?

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.

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.
Research Analyst at a university with 51-200 employees
Real User
Top 20
Straightforward to set up and has good data wrangling functionality

What is our primary use case?

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

What is most valuable?

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

What needs improvement?

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

For how long have I used the solution?

I have been using KNIME for three years.

What do I think about the scalability of the solution?

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

How are customer service and technical support?

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.

How was the initial setup?

The initial setup is…

What is our primary use case?

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

What is most valuable?

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

What needs improvement?

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

For how long have I used the solution?

I have been using KNIME for three years.

What do I think about the scalability of the solution?

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

How are customer service and technical support?

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.

How was the initial setup?

The initial setup is straightforward.

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

There are different licenses available.

Which other solutions did I evaluate?

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

What other advice do I have?

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.

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.
Professor at a university with 51-200 employees
Real User
Top 5Leaderboard
A stable teaching tool
Pros and Cons
  • "The solution is good for teaching, since there is no need to code."
  • "Both RapidMiner and KNIME should be made easier to use in the field of deep learning."

What is most valuable?

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.

What needs improvement?

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. 

For how long have I used the solution?

I have been using KNIME for more than 14 years. 

What do I think about the stability of the solution?

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

What other advice do I have?

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. 

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