KNIME Overview

KNIME is the #1 ranked solution in our list of top Data Mining tools. It is most often compared to Alteryx: KNIME vs Alteryx

What is KNIME?
KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use our open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.

KNIME is also known as KNIME Analytics Platform.

KNIME Buyer's Guide

Download the KNIME Buyer's Guide including reviews and more. Updated: June 2021

KNIME Customers
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
KNIME Video

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LL
Intern at a energy/utilities company with 10,001+ employees
Real User
Fast problem solving with minimal coding, I just drag and drop

What is our primary use case?

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.

Pros and Cons

  • "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."

What other advice do I have?

I would rate it at nine out of 10. It's good, it makes thing easier.
it_user837522
Data Science Consultant
Consultant
Very easy-to-use visual interface; Data Wrangling and looping help automate analysis

What is our primary use case?

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.

Pros and Cons

  • "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."
  • "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."

What other advice do I have?

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.
Learn what your peers think about KNIME. Get advice and tips from experienced pros sharing their opinions. Updated: June 2021.
511,607 professionals have used our research since 2012.
GM
Senior Data Scientist
Real User
Clear view of the data at every step of ETL process enables changing the flow as needed

What is our primary use case?

We use KNIME for two main reasons: Automation: The main purpose of our utilization it to run scheduled workflows (such as CRM campaigns, business reports, etc.) on a recurrent basis. We have created ETLs to automate most of the recurrent tasks and we let it run via batch files. Ad-hoc business cases: 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.

Pros and Cons

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

What other advice do I have?

I’ve been using KNIME for more than four years now. I started using it in the company I was working for in Rome (Paddy Power Italy), then I moved to headquarters in Dublin (Paddy Power Ireland/UK) and started using it for their business. Eventually, I moved to the United States and started using it for my current company (TVG-Betfair) and it is currently the main analytics tool in both our offices (New Jersey and Los Angeles). I would definitely rate it a nine out of 10. I am very happy with the product and it would be hard to find something better in the market.
it_user837516
Business Analyst at a retailer with 501-1,000 employees
Real User
Allows me to integrate several data sets quickly and easily, to support analytics

What is our primary use case?

All analytics individuals use KNIME to integrate multiple sources of data (SQL, excel, etc.) and prep the data for static reporting.

Pros and Cons

  • "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."
  • "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."

What other advice do I have?

I rate it a seven out of 10. It's very useful but needs polish and improved UX and UI in several areas. For quick adoption, either get KNIME to provide training, or have a local knowledge expert on hand who is well versed with data workflow tools, and databases if necessary.
Evans Otalor
Business Intelligence Manager at Telecoms
Real User
It has allowed us to easily implement advanced analytics into various processes

What is our primary use case?

Primarily used for advanced analytics, include designing and running predictive models, and conducting segmentation analysis. With KNIME, I connect to different data sources but usually need to conduct some data transformations before the main task is carried out. My results are usually written to a database, then I use a different tool for data visualization

How has it helped my organization?

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

What is most valuable?

Easy to use nodes for ETL processes. This is because, in many cases, I usually transform the data before the main task even when the data is from a structured database.

What needs improvement?

Data visualization.

For how long have I used the solution?

Dusty Evely
Business Analyst at a tech services company with 201-500 employees
Real User
Rule Engine allows me to create lookup tables on the fly

What is our primary use case?

I write weekly articles breaking down the previous week's Green Bay Packers' game. My main use for KNIME at this time is a workflow that takes play-by-play data from a CSV and puts it into a multi-tabbed Excel document, with all the stats I need for the week.

Pros and Cons

  • "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."
  • "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."

What other advice do I have?

Do training up front to make building workflows clean and easy from the start.
Agus Kurdiyanto
Solution Integrator at a comms service provider with 11-50 employees
Real User
Helps me collect, reformat, load data from multiple sources into one db, but needs visualization features

What is our primary use case?

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.

Pros and Cons

  • "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."

What other advice do I have?

If you like data analysis, KNIME is the best option. It's free and easy to set up.
PD
Data Scientist at a tech services company with 1,001-5,000 employees
Real User
We have been able to appreciate the considerable reduction in prototyping time

What is our primary use case?

We have used KNIME for text processing, specifically for leveraging the text processing features for entity extraction, document classification, relationship extraction, and other such NLP tasks.

How has it helped my organization?

We are far from reaping the benefits of this platform as an organization. However, so far, we have been able to appreciate the considerable reduction in prototyping time.

What is most valuable?

The most useful features are the readily available extensions that speed up the work. For instance, KNIME offers multiple document taggers, which one can use with relative ease. Similarly, the number of predefined NER taggers are also very handy.

What needs improvement?

The documentation needs a proper rework. 

For how long

it_user461148
Partner, Turkey and The Netherlands at a tech vendor with 201-500 employees
Real User
Our average record size was around 10 million records. If we have bigger data, we can opt for a Big Data extension for Hadoop, Spark, etc.

What is our primary use case?

In demand forecasting projects to extract, to clean and to transform data from various resources. Also some clustering and classification techniques are used for behavioural clustering and classification according to attributes.

What other advice do I have?

Data Science requires freedom for creativity. Sometimes you need to crawl data from the web or social media. Sometimes you need to blend different sources like NoSQL MongoDB and Excel files, etc. It is not only algorithms and data extraction, visualization and preparation steps are important as at least algorithms. Don't go with software that has complex and hidden licensing costs, which will kill your flexibilty and creativity. Also, interoperability brings the advantage of limitlessness.
Dharma Teja
Associate Analyst at a consultancy with 1,001-5,000 employees
Consultant
Easy to setup, it organises workflows in very neat manner

Pros and Cons

  • "Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
  • "System resource usage. Knime will occupy total system RAM size and other applications will hang."

What other advice do I have?

It is best one for harmonizing data with no cost included.
ITCS user
CEO with 11-50 employees
Vendor
The diversity of native algorithms could be improved but it is very easy to use​
Buyer's Guide
Download our free KNIME Report and get advice and tips from experienced pros sharing their opinions.
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