Databricks vs Saturn Cloud comparison

Databricks and Saturn Cloud are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.4, while Saturn Cloud is ranked #14 with an average rating of 10.0. Databricks holds a 13.9% mindshare in Data Science Platforms, compared to Saturn Cloud’s 0.3% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Saturn Cloud users who would recommend it.

Databricks

Read 91 Databricks reviews

20,775 Views
8,933 Comparison Views

96% willing to recommend

Saturn Cloud

Read 6 Saturn Cloud reviews

470 Views
179 Comparison Views

100% willing to recommend

Databricks

Saturn Cloud

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Databricks and Saturn Cloud are both influential products in the data processing and machine learning sector. Databricks holds a competitive advantage in pricing and support, attracting those mindful of costs, whereas Saturn Cloud's functionality and scalability make it appealing to users seeking potent features.

Features: Databricks offers seamless data integration, collaborative workspaces, and robust cloud-based analytics capabilities, making it suitable for complex data analysis. Saturn Cloud emphasizes scalability, rapid environment deployment, and ease of use, catering to users requiring flexibility and fast setups.

Room for Improvement: Databricks could improve by simplifying its initial deployment complexity and reducing setup costs to enhance accessibility. Additionally, offering more intuitive user interfaces could benefit newer users. Saturn Cloud may enhance its support for integration with additional big data tools and could provide more comprehensive documentation to help new users understand the platform's full potential.

Ease of Deployment and Customer Service: Saturn Cloud is distinguished by its user-friendly setup and strong customer support, which simplify deployment for quick scalability. Databricks offers a comprehensive deployment model, although its initial setup can be complex, necessitating more oversight but ultimately providing significant long-term advantages.

Pricing and ROI: Databricks generally presents higher initial setup costs but ensures substantial ROI through comprehensive data processing and scalability. Saturn Cloud offers competitive pricing, making it attractive for budget-conscious organizations seeking cost-effective flexibility with strong ROI potential.

To learn more, read our detailed Databricks vs. Saturn Cloud Report (Updated: September 2025).

Buyer's Guide

Databricks vs. Saturn Cloud

September 2025

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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

Databricks

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Streaming Analytics (1st)

Saturn Cloud

Ranking in Data Science Platforms

14th

Average Rating

10.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Databricks is 13.9%, down from 19.2% compared to the previous year. The mindshare of Saturn Cloud is 0.3%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	13.9%
Saturn Cloud	0.3%
Other	85.8%

Data Science Platforms

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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Alessandro Trinca Tornidor

Sviluppatore software at TeamSystem

Good for creating POCs, training machine learning models, and experimenting without local resources

The project I’m currently working on relies on CUDA, but my local PC does not have any Nvidia GPUs. I’ve found the computational resources and ease of use provided by Saturn Cloud invaluable. Also, there are many ready-to-use Docker images and a rich documentation portal with useful examples. The dashboard for creating a new virtual environment contains almost all the features I needed: environment variable definitions, git repositories cloning directly from the new resources page, and an edit field to define a custom script during the boot process. For this reason, Saturn Cloud.io is a very good solution for creating POCs, training machine learning models, and generally experimenting a bit without worrying about local resources.

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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

"It is fast, it's scalable, and it does the job it needs to do."

"The most valuable feature is the ability to use SQL directly with Databricks."

"The solution is built from Spark and has integration with MLflow, which is important for our use case."

"The solution is very simple and stable."

"I haven't heard about any major stability issues. At this time I feel like it's stable."

"Databricks has helped us have a good presence in data."

"The load distribution capabilities are good, and you can perform data processing tasks very quickly."

"The time travel feature is the solution's most valuable aspect."

More Databricks pros

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

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

"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."

"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."

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

Cons

"The integration and query capabilities can be improved."

"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."

"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."

"The tool should improve its integration with other products."

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"The connectivity with various BI tools could be improved, specifically the performance and real time integration."

"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."

"Databricks can improve by making the documentation better."

More Databricks cons

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

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

"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."

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

Pricing and Cost Advice

"Databricks uses a price-per-use model, where you can use as much compute as you need."

"The product pricing is moderate."

"The solution is based on a licensing model."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

"I would rate Databricks' pricing seven out of ten."

"The price of Databricks is reasonable compared to other solutions."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

More Databricks pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

Manufacturing Company

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

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

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

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How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

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What do you like most about Saturn Cloud?

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

See all answers

What needs improvement with Saturn Cloud?

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 ...

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

Comparisons

Microsoft Power BI vs Databricks

Compared 9% of the time

Dataiku vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 5% of the time

Tableau Enterprise vs Databricks

Compared 4% of the time

More Databricks Competitors

Amazon SageMaker vs Saturn Cloud

Compared 100% of the time

More Saturn Cloud Competitors

Product Reports

Buyer's Guide

Databricks

October 2025

Download Databricks product report

Buyer's Guide

Saturn Cloud

September 2025

Download Saturn Cloud product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

Databricks

Saturn Cloud is a cloud-based data science and machine learning platform that provides a scalable, flexible, and easy-to-use environment for data scientists and machine learning engineers. Saturn Cloud offers a variety of features and tools for data science, including: Compute resources (including CPUs, GPUs, and Dask clusters), Storage (object, block, and ephemeral storage), Networking, a variety of integrations with ML tools such as JupyterLab, RStudio, and TensorFlow.

Saturn Cloud is a good choice for data scientists and machine learning engineers who need a scalable, flexible, and easy-to-use environment.

Saturn Cloud also makes it easy to collaborate with other data scientists and machine learning engineers. You can share projects, notebooks, and data with others, and you can track changes to your work.

Saturn Cloud

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

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

Buyer's Guide

Databricks vs. Saturn Cloud

September 2025

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