KNIME Business Hub Reviews

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

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

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

I have been using KNIME for three years.

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

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.

The initial setup is straightforward.

There are different licenses available.

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

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.

I am a basic user, doing a data science course.

I am using Knime more from a study perspective, rather than a practical work application.

I am fairly competent with creating workflows and automating some basic things in Knime.

NA

From a user-friendliness perspective, it's a great tool.

I think some of the online training content could be better, although I have been able to find all of the information. At times they're quite lengthy, and for me to go through everything and then get a resolution takes a good amount of time.

They could have a more structured node-wise training model, where I can simply get into it. For example, if I need to understand a node to create pivot tables, I have to go through the training mode to understand what the functionality is.

If they had a more structured training model it would be very helpful.

It would be helpful to launch more certification programs online. 

There could be better marketing. The awareness of Knime is limited, especially for small organizations. When you compare with PowerBI, there is a lot of active marketing put into their product, also, having Microsoft associated with it is an advantage.

They have to step up on the marketing aspect and the ability to digitize using Knime. Many are aware of other tools such as PowerBI.

In the next release, I would like to see the certification available for active users.

Also the costing aspect of the certification, there could be more local impact time zone programs with a bit of costing dissension to encourage more active users in Knime who can then move to the server version in their organization.

I have been using Knime for approximately one year.

We are in the testing phase of this solution.

It is quite stable. I have not been faced with any issues since I have been using this solution.

Knime is a scalable product.

We have five power users who are test prototype users at the moment. We are trying to sell that prototype to the management so that we can deploy it on a larger scale.

I have never had the need to reach out to technical support.

At some point when I move on with the server versions, I might need some help.

The desktop version, it's more of an install and then just run it.

At this time, I am using the free version of Knime.

I did look at Tableau and was considering it to some extent. I felt Knime was more user-friendly and more versatile to automate tasks (most of them excel based).

I am quite supportive of this product. It has been helpful in automating a few of my accounting activities.

Digital groups such as Knime have great potential, but there needs to be more aggressiveness with marketing. There are many executives that do not know what Knime is.

My journey starts by explaining what Knime is and what the functionalities are.

I like Knime, and I would rate this solution a nine out of ten.

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.

I am advocating the use of this solution in my organization. I use it personally for my purposes and for the company, I use it for internal data science with very good results.

What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.

It is difficult to say at this time, as I am not using the latest version. I have noticed that I don't have the latest modules that were added, such as ML.

In my opinion, there's one thing lacking. As far as algorithm notes go, it would be handy if category algorithms of C4 or C4.5 could be set with a checkbox or something like that.

Once you go to the forum or the documentation, to see how to implement a C4.5, you mark the checkbox, and only then it would be content for C4 or C4.5.

The documentation is lacking and it could be better. It's a community-driven product but there are a few crucial models missing such as ANOVA and MANOVA.

I have been using KNIME since December 2019.

In my opinion, it is very stable.

I have not yet explored the scalability as I am using it on my local machine and I don't have the experience of putting it on the cloud.

I do plan to increase my usage.

The documentation is okay, although there are things missing. At the same time, the forum support is great.

Previously, I was using SPSS Statistics, although that was ten years ago. I had a gap in data mining and the statistic field as a whole.

The initial setup is very straightforward.

It's an open-source solution.

I am considering further courses and maybe some certification in the next year.

I would strongly recommend KNIME. It's a modeling or statistics product that can be used by almost anyone with knowledge in the field. It works almost out of the box.

For starters, it's approximately two hours of watching videos and/or reading the documentation, and then off you go.

I built my first working model in two days when I started using KNIME, and it only needed to be tweaked. It was impressive.

I would rate this solution an eight out of ten.

We are a solution provider and KNIME is a product that we are working on reselling to our customers. We sell BI tools such as Tableau and many of our customers that are using these tools need to have an AI solution. They have lots of use cases for AI including, for example, those from the financial sector would like to use AI for credit scoring. We also have government clients who will have their own specific use cases.

We have not yet sold it to any of our customers because they are still using the free tools and we are promoting it based on that.

The nicest part of KNIME is that the designer tool is free.

This solution is easy to use and it can be used to create any kind of model.

We are worried about the performance when it comes to using a lot of data that has many rows and columns. On the server-side, we are not sure whether KNIME can manage or handle large amounts of data without issue. It looks like it will easily work for small datasets but we are concerned about performance as the volume increases.

KNIME needs to provide more documentation and training materials, including webinars or online seminars. At this time, it is not sufficient when compared to some other vendors.

The user interface needs to be improved because it looks quite messy and I am not very comfortable using it. 

I have been familiar with KNIME for two or three years but we have been actively interested in it for less than a year.

We have not deployed the entire solution for a customer yet. However, we have been working with the design tool, which does not require deployment. You just have to download it and then it can be used for testing demonstration data.

The price of KNIME is quite reasonable and the designer tool can be used free of charge.

Many of our customers have streaming data and want to use an AI model. We do not yet know whether KNIME will handle live-streaming and it is something that we intend to test.

I would rate this solution a seven out of 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.

Our primary use case for this solution is shopping-basket analysis.

It gives much insight about business in different aspects, from understanding product portfolio to clients, much of them arouse interests from important stakeholders

It is a complete data science platform and especially good at scaling up data preparation and wrapping. It provides a large numbers of algorithms to look at data from different angles

It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end.  The learning curve is steep.

We have been using this solution for six months.

Very good

Perfect

Very good and very prompt, usually in a few hours, can't complain more

I wrote Python in different IDE, however KNIME is easier to tackle with changes in data sources, processes, and expectations, etc. It is simple to work around with different situations for testing and comparison. 

Setup is very easy, no more than a normal app

I do it myself, and I am super-user level

More than worthy to invest

One of the benefit for KNIME is free for desktop version, which is enough for small team work. It is worthy to try but prepare for times to search and learn. It is not really as easy as drag and drop.

I check with Alteryx and RapidMiner

Official and structural online training is a must, which is now not enough. Or you can start something simple very easily but stuck to go deeper. However KNIME response is very prompt.

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.

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.

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.

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.

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

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

Scalability is limited to a desktop application.

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

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.

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

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.

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

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.