KNIME Reviews

Providing the right solutions and consulting in revenue management requires rapid and comprehensive analysis in all areas. Such analysis makes it easier to look for patterns, where and when the cause of a problem is, especially when the solution has hundreds or more servers of different types and characteristics.

I use KNIME as a tool (ETL) in processing various logs and data (structured and unstructured format) then analyze and store the information in a database. This makes it easier to do the analysis and saves me time.

It very much helps me to do my job while supporting my organization's delivery of service to our client.

Most important, it is open-source. Next is the ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database.

I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports.

In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations.

I feel the query performance is slower than my old code. In my configurations, I set concurrence for a heavy query database, from multiple database sources, then transformed it before loading it into a destination database. It cannot do concurrent writing into databases if I use one database connection (user).

I’m not sure it is a lack in KNIME or in the database driver itself. To prevent the degredation of performance and system stability, I need to change the configuration of databases readers for output, write parameter onto the disk, not into memory.

I have never used tech support, but the community forums are quite good. Hopefully, there will be a knowledgebase, like VMware did.

I created my own script. I switched to KNIME because it simplifies the flow of my script into one workspace, and doesn't necessitate a lot of jobs in my system.

No, KNIME is my first choice because it's open-source and has features to combine with other scripts.

If you like data analysis, KNIME is the best option. It's free and easy to set up.

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 mainly used it to perform predictive modeling projects, such as customer-churn predictions and HR attrition predictions. The environments are mainly SQL-databases or CSV files.

The installation I worked with to perform the analyses was a regular laptop with no computational server behind it, which may have an impact on the capacity of the program handling very large databases or files.

The clients I performed the analyses for were all very pleased with the results. For churn prediction, one of the companies proactively started contacting clients with high risk to churn, resulting in drastically decreasing churn rates.

For organizations with a small team of data analysts or data scientists, it is a very easy tool to become familiar with predictive modeling, and makes it possible to hand over projects to colleagues without the need to extensively document them.

• The very easy-to-use visual interface
• Help functions and clear explanations of the functionalities and the used algorithms
• Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis

For inexperienced analysts or data scientists, it is a very easy tool to take your first steps in modeling and analytics.

The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R).

The program is not fit for handling very large files or databases (greater than  1GB); it gets too slow and has a tendency to crash easily.

I used it quite intensively for 10 months, long enough get familiar with it, to follow training, to use it in in several projects, to ask questions on the user forum.

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 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.

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.

Data preparation and data modeling are easy to do.

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. 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.

We have been working with Knime for approximately one year.

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

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

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

The initial setup is easy.

The price for Knime is okay.

I would rate this solution a nine out of ten.