Dataiku vs Saturn Cloud comparison

Dataiku and Saturn Cloud are both solutions in the Data Science Platforms category. Dataiku is ranked #2 with an average rating of 8.1, while Saturn Cloud is ranked #19 with an average rating of 10.0. Dataiku holds a 5.6% mindshare in Data Science Platforms, compared to Saturn Cloud’s 1.2% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Saturn Cloud users who would recommend it.

Dataiku

Read 21 Dataiku reviews

6,883 Views
6,745 Comparison Views

100% willing to recommend

Saturn Cloud

Read 6 Saturn Cloud reviews

1,863 Views
671 Comparison Views

100% willing to recommend

Dataiku

Saturn Cloud

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Executive SummaryUpdated on Dec 5, 2024

Dataiku and Saturn Cloud are both leaders in the data science and machine learning sector. While Dataiku shines with its collaborative capabilities, Saturn Cloud's strength lies in offering scalability and advanced computational options.

Features: Dataiku provides tools for team collaboration, intuitive data preparation, and automated machine learning processes, enabling seamless interaction among team members. Saturn Cloud offers high-performance computing abilities, scalability with GPU support, and Dask-powered data handling, focusing on meeting computational demands efficiently.

Room for Improvement: Dataiku could enhance its scalability options and GPU support to cater to more computationally intensive projects. Additionally, integrating some high-performance computing features might add value. Saturn Cloud may improve by incorporating more collaborative features and user-friendly interfaces. Enhancing options for hybrid deployment could also broaden its applicability across different business environments.

Ease of Deployment and Customer Service: Dataiku offers both on-premise and cloud deployment, providing flexibility in setup options. Its customer service is responsive, ensuring user queries are addressed promptly. Saturn Cloud primarily supports cloud deployment, with straightforward scaling facilities that appeal to cloud-dependent organizations. Both platforms offer commendable support, though Dataiku's diverse deployment methods give it an edge.

Pricing and ROI: Dataiku's high initial setup costs might be offset by the return on investment through efficient project completion and strengthened team collaboration. Saturn Cloud provides scalable pricing models, making it cost-effective for large-scale computational needs. While Dataiku requires a higher upfront investment, its collaborative tools often justify the expense, whereas Saturn Cloud's pricing aligns well with projects requiring scalability and vast computational resources.

To learn more, read our detailed Dataiku vs. Saturn Cloud Report (Updated: April 2026).

Buyer's Guide

Dataiku vs. Saturn Cloud

April 2026

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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

2nd

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Saturn Cloud

Ranking in Data Science Platforms

19th

Average Rating

10.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.6%, down from 12.8% compared to the previous year. The mindshare of Saturn Cloud is 1.2%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	5.6%
Saturn Cloud	1.2%
Other	93.2%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly

In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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Filip Stefanovski

Works at a tech consulting company with 51-200 employees

Easy to use with good performance and collaborative features

My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer. Users could bid on unused compute capacity, potentially leading to significant cost savings during off-peak hours or for less time-critical tasks. Spot instances empower users with tighter budgets or fluctuating workloads to strategically leverage lower-cost resources for development, experimentation, and background tasks. This frees up on-demand instances for truly time-sensitive work.

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Quotes from Members

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

Pros

"One of the valuable features of Dataiku is the workflow capability."

"Dataiku has positively impacted my organization, specifically in one project where we performed migration from AWS to Dataiku, speeding up the solution by close to 40% and reducing architecture costs by almost 70%, which was a significant benefit and greatly impacted our operations."

"The best feature in Dataiku is that once the data is connected in the underneath layer, it flows exceptionally smoothly if you know how to tweak it."

"The best features Dataiku offers that help me with my demand forecasting and data science projects include having a complete overview of the flow directly from the flowchart, allowing me to observe all the steps in a single overview, and the ability to use a no-code, low-code node."

"Dataiku is highly regarded as it is a leader in the Gartner ranking."

"I like the interface, which is probably my favorite part of the solution; it is really user-friendly, colorful, and I think it is really beautiful and well-designed."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"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."

More Dataiku pros

"The feature I like the most about Saturn Cloud is that it has lightning-fast CPUs."

"Saturn Cloud supports GPU as part of the environment, which is essential for many computational tasks in machine learning projects. It also allows us to edit the environment, including the image, before we start the cloud resources. This feature lets us quickly set up the environment without the hassle of moving the data and code to another cloud device."

"There is plenty of computational resources (both GPU, CPU and disk space)."

"They provide a centralized space for data, code, and results."

"It offered an excellent development environment while not touching our production cloud resources."

"It didn't take long to see that Saturn Cloud could scale with my needs, providing more resources when required."

Cons

"Dataiku is down a lot of times, and we have to wait for sometimes five, ten, or fifteen minutes, after which it gets working again, and during those times, we are unable to get our work done."

"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."

"All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex."

"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."

"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 license is very expensive."

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

More Dataiku cons

"We'd like to have the capability for installing more libraries."

"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."

"Providing more detailed and beginner-friendly documentation, especially for advanced features, could greatly enhance the user experience."

"Public Clouds integration and sandbox environments would be a true game changer."

"Saturn Cloud should include prebuilt images for advanced data science packages like LightGBM in the next release. If possible, they should also provide a Kaggle image, which contains the most common Python packages used in machine learning."

"My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer."

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."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

Computer Software Company

Energy/Utilities Company

Construction Company

30%

Healthcare Company

10%

Financial Services Firm

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	13

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	1
Large Enterprise	3

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my personal projects, I used the thirty-day free trial. Regarding my company, I did not ha...

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What needs improvement with Dataiku Data Science Studio?

I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the server is full or what, but it sometimes takes a lot of time while loading and re...

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What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that. For ETL pipelines and data analysis, I had to create the output by combining a...

See all answers

What needs improvement with Saturn Cloud?

See all answers

What is your primary use case for Saturn Cloud?

I'm leveraging a cloud-based platform for competitive machine learning. Tight deadlines and resource-intensive models demand powerful hardware. The cloud provides scalable GPUs and RAM, letting me ...

See all answers

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Product Reports

Buyer's Guide

Dataiku

May 2026

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Buyer's Guide

Saturn Cloud

April 2026

Download Saturn Cloud product report

Also Known As

Dataiku DSS

No data available

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

Saturn Cloud is a platform optimized for machine learning tasks with tools for distributed computing and resource scalability. With its support for multiple programming languages and libraries, it provides an environment conducive to experimentation and prototyping.

Saturn Cloud offers a high-performance computing experience with Dask cluster support, facilitating distributed computing and resource scaling. The integration with Jupyter environments allows seamless transitioning for users accustomed to using these tools. The platform provides GPU support, which is particularly beneficial for projects involving reinforcement learning and deep learning. Users have found the pre-configured environments and GitHub integration valuable in streamlining setup, prototyping, and testing processes, enhancing overall efficiency. Customization through Docker images, SSH access, and the availability of free computing resources provide added flexibility and cost-effectiveness.

What are Saturn Cloud's essential features?

Dask Cluster Support: Enables easy distributed computing across projects.
Resource Scaling: Provides flexible adjustment of computational resources.
Integration with Jupyter Environments: Supports smooth collaboration and use of familiar tools.
GPU Support: Offers enhanced processing power for machine learning tasks.
Customization via Docker: Allows personalized environments and setups.

What benefits can users expect from Saturn Cloud?

Fast Setup: Quick to configure and begin using, speeding up the development process.
Cost-Effective Computing: Offers free resources and flexible pricing options.
Collaborative Features: Shared folders for seamless team collaboration.
Efficient Experimentation: Facilitates prototyping and testing with pre-configured environments.

In industries where scalable resources are critical, such as tech and data analysis, Saturn Cloud supports projects like Optical Character Recognition (OCR) and image segmentation. Its cloud-based storage and multi-core computation capabilities are essential for handling data-intensive tasks, making it a favored choice among professionals handling extensive machine learning models and experiments.

Saturn Cloud

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

Nvidia, Snowflake, Kaggle, Faeth, Advantest, Stanford University, Senseye and more.

Buyer's Guide

Dataiku vs. Saturn Cloud

April 2026

Free Report: Dataiku vs. Saturn Cloud

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