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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
8.0
Reviews Sentiment
7.1
Number of Reviews
59
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.7%, up from 8.2% compared to the previous year. The mindshare of KNIME is 11.7%, up from 9.8% 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

"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"The solution is quite stable."
"The most valuable feature is the set of visual data preparation tools."
"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 believe the return on investment looks positive."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"I rate the overall product as eight out of ten."
"Our clients can easily drag and drop components and use them on the spot."
"It's a huge tool with machine learning features as well."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"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."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"From a user-friendliness perspective, it's a great tool."
"KNIME is quite scalable, which is one of the most important features that we found."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"We have found KNIME valuable when it comes to its visualization."
 

Cons

"I think it would help if Data Science Studio added some more features and improved the data model."
"We still encounter some integration issues."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"There is room for improvement in terms of allowing for more code-based features."
"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."
"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."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"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."
"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."
"For graphics, the interface is a little confusing."
"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."
"The graphic features of KNIME need improvement"
"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."
"The current UI is primarily in English. Analyzing data in local languages might present challenges or issues."
"KNIME could improve when it comes to large data markets."
 

Pricing and Cost Advice

"Pricing is pretty steep. Dataiku is also not that cheap."
"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."
"KNIME Business Hub is expensive for small companies."
"This is a free open-source solution."
"It is free of cost. It is GNU licensed."
"At this time, I am using the free version of Knime."
"There is a Community Edition and paid versions available."
"The price of KNIME is quite reasonable and the designer tool can be used free of charge."
"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."
"I use the tool's free version."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Educational Organization
14%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
13%
Manufacturing Company
11%
Computer Software Company
9%
University
7%
 

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?
The pricing for Dataiku is very high, which is its biggest downside. The model they follow is not consumption-based, making it expensive.
What needs improvement with Dataiku Data Science Studio?
Dataiku's pricing is very high, and commercial transparency is a challenge. Support is also an area needing improvement. More features like LLM security, holographic encryption, and enhanced GPU in...
What is your primary use case for Dataiku Data Science Studio?
My primary use case for Dataiku ( /products/dataiku-reviews ) is for data science, Gen ( /products/gen-reviews ) AI, and data science applications. Our AGN team also uses it for various purposes.
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?
For graphics, the interface is a little confusing. So, this is a point that could be improved.
 

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: March 2025.
845,406 professionals have used our research since 2012.