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Dataiku vs KNIME comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
6th
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
KNIME
Ranking in Data Science Platforms
2nd
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of May 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.8%, up from 8.4% compared to the previous year. The mindshare of KNIME is 11.9%, up from 9.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
Laurence Moseley - PeerSpot reviewer
Has a drag-and-drop interface and AI capabilities
It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The most valuable feature is the set of visual data preparation tools."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"I believe the return on investment looks positive."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"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."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"Since KNIME is a no-code platform, it is easy to work with."
"It's a coding-less opportunity to use AI. This is the major value for me."
"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."
"It is very fast to develop solutions."
"Stability is excellent. I would give it a nine out of ten."
 

Cons

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"I think it would help if Data Science Studio added some more features and improved the data model."
"We still encounter some integration issues."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"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."
"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 graphic features of KNIME need improvement"
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"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."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"The documentation needs a proper rework. ​"
 

Pricing and Cost Advice

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"Pricing is pretty steep. Dataiku is also not that cheap."
"KNIME Business Hub is expensive for small companies."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"The price for Knime is okay."
"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."
"KNIME is a cost-effective solution because it’s free of cost."
"I use the tool's free version."
"There is a Community Edition and paid versions available."
"It is expensive to procure the license."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
10%
Computer Software Company
9%
Manufacturing Company
9%
Financial Services Firm
12%
Manufacturing Company
11%
Computer Software Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.
What needs improvement with Dataiku Data Science Studio?
There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend ...
What is your primary use case for Dataiku Data Science Studio?
My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are uti...
What do you like most about KNIME?
Since KNIME is a no-code platform, it is easy to work with.
What is your experience regarding pricing and costs for KNIME?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with KNIME?
I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer version, 5.4, when it becomes available. The machine learning and profileration asp...
 

Comparisons

 

Also Known As

Dataiku DSS
KNIME Analytics Platform
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Dataiku vs. KNIME and other solutions. Updated: April 2025.
851,604 professionals have used our research since 2012.