KNIME Reviews

We use KNIME for data and manipulation.

We have found KNIME valuable when it comes to its visualization.

We have been using KNIME for the past five years.

KNIME is stable for our needs after using it for five years.

KNIME is not scalable.

I have had no need to contact technical support.

I have used Python. The logic is the same, but the interface is totally different.

The setup for KNIME is simple. I would rate the setup a five on a scale of one to five.

I would rate KNIME a seven on a scale of one to ten.

We used the product to prepare data for our team. I would prepare SQLs and check them in Oracle Developer, then create workflows in KNIME to manage and process the data, creating specific tables for modeling.

The product is a great alternative because it is not an open-source tool and offers simplicity, making it easier for our large team to use.

Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters. Breaking up SQLs was necessary to handle the data flow better.

I extensively used KNIME for about one year and at least two months.

The product is quite stable.

The platform is scalable. It is possible to configure the system to effectively manage memory and space requirements. 

I rate the scalability a seven out of ten. 

The community support is good, and plenty of shared knowledge is available.

We had licensing issues with other tools, but KNIME worked well as an alternative.

We integrated KNIME with Oracle, Apache, and other tools. It allowed us to pull data from various sources, such as Oracle, CSV, and Excel, into one consolidated table, which was very efficient.

Overall, I rate it an eight. It is a good tool, especially for our current requirements. However, there were limitations, such as space issues and occasional process slowdowns due to memory constraints. Despite these challenges, it is a solid product.

I recommend it to other professionals, particularly those who work with diverse datasets and require a flexible tool to manage data flows. It is user-friendly, especially for individuals with a background in Java or Python, as it allows for custom operations and automation, which I found very helpful in my experience.

We used the solution for data analysis. With the help of its graphical workflow interface, we were able to identify the exact logic behind the source code.

The solution is the best data science tool if you gain in-depth knowledge about its functions.

They should improve the solution's integration with other platforms. Also, they should add more functions to its server.

We have used the solution for less than a year.

I rate the solution's stability as a seven as we face memory leakage issues.

We have nine users of the solution in our organization. I rate its scalability as a nine, as we can deploy it in a cluster.

We used Rapidminer earlier. We switched to KNIME as it is a better tool for data mining.

The solution's initial setup is easy. The process takes several minutes to complete with a good network connection.

We have a technology tool to help us install the solution.

You must have the essential knowledge to solve the solution's compliance issues. It could be easier to use and integrate with other products.

I recommend the solution to others and rate it as a seven.

KNIME is mainly used for developing workflows for machine learning and VA. We are using integrated Python scripts.

The solution has improved our company because it is economical as it is an open-source platform. There are not a lot of costs involved.

The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way.

I want to access more of the popular deep learning libraries or frameworks as they have in other solutions, such as TensorFlow and PyTorch. There should be better integration, and a better way to use those libraries because they are very popular. Our company uses PyTorch and TensorFlow regularly to solve many computer vision problems. We expect better integration of those two tools.

KNIME could improve when it comes to large data markets.

I have been using KNIME for approximately one and a half years.

The solution is stable but it could improve.

I rate the stability of KNIME a six out of ten.

We have approximately 25 people using this solution in my company. The employees typically do business analytics with MLS and DLLs in their workflow.

We are not using the solution at its full capacity.

I rate the scalability of KNIME a six out of ten. 

I have not contacted the support from KNIME directly. We use online forums and blogs.

We used Alteryx prior to KNIME.

We do the deployment of the solution in-house. We have a team of approximately five to seven people who not only take care of these pipelines, and workflows in this solution, but also do a lot of AI and ML module developments.

This is a free open-source solution.

We selected KNIME rather than Alteryx because of the price comparison.

We usually only use the coding methods using Python. When people don't have much experience with coding, then we always recommend they choose the concepts of analytics and machine learning, mainly a no-code tool, such as KNIME or Alteryx. They become close to citizen developers. We will teach them coding aspects later. They always start with a no-code or a low-code tool, such as KNIME and Alteryx. Once they learn slowly, we switch them over to coding access.

I would recommend this solution for use cases that has a small amount of data and not a lot of code needed.

I rate KNIME a six out of ten.

We use this solution primarily for automation processing, source data, and for data lake or databases. 

I like the visual features and that we can connect using a pixel or an icon for the sources and controls. KNIME is easy to use, it's stable, powerful, and has a lot of features.

For now, the license is quite expensive for us and it would be helpful if that was reduced.

I've been using this solution for a few years. 

The solution is stable. 

We have five people using this solution so we haven't yet tested the scalability. 

We use the community for any questions we have. 

I think the deployment requires a specialist but once it's implemented it doesn't need any maintenance. 

We use the community version; the enterprise version is expensive for us. If we need better support or have other requirements we might need to move to the enterprise version. 

I rate this product nine out of 10. 

KNIME is used for collecting data for data science.

KNIME has improved our organization because we are able to collect data in a way that we can interpret and it provides visuals.

Overall KNIME serves its purpose and does a good job.

KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile.

I have been using KNIME for approximately four years.

KNIME is stable.

KNIME is always highly scalable, as new features come out and things that we learn from the new features can help us interpret data better.

We have approximately 12 people using the solution. There are three groups of users, the data entry team, data collection experts, and data interpreters. They use the solution for two months for each project we work on. We are planning on hiring more data scientists.

I rate the support from KNIME a three out of five.

I have not used other solutions other than KNIME.

The initial setup of KNIME was not challenging, but it took some practice.

The full deployment took us approximately one year. It took us a little while to adjust to the solution because many of the users did not have an analytics background, we had to teach them.

I rate the ease of setup for KNIME a four out of five.

We did evaluate other solutions. We decided to use KNIME because it is open source and was easier to start with.

My advice to others is to start out slow and gradually increase operations. 

I rate KNIME an eight out of ten.

There are other applications that I've used that make collecting the data and interpreting it a lot easier. If they could improve this my rating would increase.

We are users of KNIME and we also resell this product.

The primary use case is for data analysis.

KNIME has a good set of features for data analytics.

The sampling features are some of the most important ones for us.

Compared to the other data tools on the market, the user interface can be improved.

There are quite a few features that are not available in the Community Edition. Having more of these features brought into the platform would be helpful.

Support from KNIME could be enhanced, although the community support is great.

I have been working with KNIME for between three and four years.

It has been stable for a while, since the release of version 4. However, between version 2 and version 3, it was quite unstable. The stability has improved.

KNIME is quite scalable, which is one of the most important features that we found.

The support for KNIME is good, although it comes from the community rather than from KNIME itself.

The initial setup is quite simple, especially if you have already worked on other tools.

The deployment can be completed within a couple of hours, including the setup of permissions and other configurations.

There is a Community Edition and paid versions available.

For anybody who is looking for a new data science platform, KNIME is a product that I can recommend.

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.