KNIME Pros and Cons

This open-source product can compete with category leaders in ELT software.

The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database.

I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data.

Clear view of the data at every step of ETL process enables changing the flow as needed.

We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders.

The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine.

Easy to connect with every database: We use queries from SQL, Redshift, Oracle.

We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics.

Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server.

Key features include: 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.

It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop.

It has allowed us to easily implement advanced analytics into various processes.

We have been able to appreciate the considerable reduction in prototyping time.

The most useful features are the readily available extensions that speed up the work.

This solution is easy to use and especially good at data preparation and wrapping.

The ability to handle large amounts of data and performance in processing need to be improved.

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'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something.

​The data visualization part is the area most in need of improvement.

The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best.

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.

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.

Data visualization needs improvement.

The documentation needs a proper rework. ​

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.