Databricks vs SAS Enterprise Miner comparison

Databricks and SAS are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.3, while SAS is ranked #18 with an average rating of 9.0. Databricks holds a 15.9% mindshare in Data Science Platforms, compared to SAS’s 0.9% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Databricks

Read 91 Databricks reviews

25,542 Views
11,494 Comparison Views

96% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

842 Views
598 Comparison Views

93% willing to recommend

Databricks

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and Databricks are competing products in the data analysis space. Databricks is often viewed as a superior product due to its advanced features and scalability, offering more flexibility in various data environments.

Features: SAS Enterprise Miner offers robust predictive analytics, extensive model management capabilities, and a vast range of statistical operations. Databricks, meanwhile, provides seamless integration with big data tools, a collaborative workspace for data engineering tasks, and advanced machine learning functionalities.

Room for Improvement: SAS Enterprise Miner could enhance its scalability and cloud integration. An improvement in the user interface for modern usage patterns would be beneficial. Additionally, expanding machine learning features could add value. For Databricks, better offline capabilities would augment its utility in areas with limited internet access. Improving the intuitive nature of certain advanced settings could be beneficial, as well as offering more detailed built-in analytics reporting.

Ease of Deployment and Customer Service: SAS Enterprise Miner is traditionally deployed on-premise, offering comprehensive support services, extensive documentation, and direct phone support, which benefits enterprise setups. Databricks provides cloud-based deployment, enabling faster scalability and updates. Its wide range of online resources and community support reflect a cloud-native approach, offering flexibility and community-driven solutions.

Pricing and ROI: SAS Enterprise Miner generally involves a higher upfront setup cost with predictable long-term expenses, catering to enterprises seeking stable financial commitments. Databricks employs a pay-as-you-go pricing model, which can be more economical for dynamic workloads and provides greater flexibility, potentially leading to higher returns through efficient resource use.

To learn more, read our detailed Databricks vs. SAS Enterprise Miner Report (Updated: June 2025).

Buyer's Guide

Databricks vs. SAS Enterprise Miner

June 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 (8th), Streaming Analytics (1st)

SAS Enterprise Miner

Ranking in Data Science Platforms

18th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of July 2025, in the Data Science Platforms category, the mindshare of Databricks is 15.9%, down from 19.8% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.9%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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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

"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."

"In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."

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

"The solution offers a free community version."

"It offers AI functionalities that assist with code management and machine learning processes."

"Databricks offers various courses that I can use, whether it's PySpark, Scala, or R."

"The simplicity of development is the most valuable feature."

"The ability to stream data and the windowing feature are valuable."

More Databricks pros

"I like the way the product visually shows the data pipeline."

"The technical support is very good."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"The solution is very good for data mining or any mining issues."

"Good data management and analytics."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

More SAS Enterprise Miner pros

Cons

"Pricing is one of the things that could be improved."

"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."

"Performance could be improved."

"There are no direct connectors — they are very limited."

"Databricks' technical support takes a while to respond and could be improved."

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

"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 stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."

More Databricks cons

"The visualization of the models is not very attractive, so the graphics should be improved."

"The product must provide better integration with cloud-native technologies."

"The ease of use can be improved. When you are new it seems a bit complex."

"The solution is much more complex than other options."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"The user interface of the solution needs improvement. It needs to be more visual."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"Virtualization could be much better."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"I rate the price of Databricks as eight out of ten."

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

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."

"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."

"Price-wise, I would rate Databricks a three out of five."

"We're charged on what the data throughput is and also what the compute time is."

"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."

"We only pay for the Azure compute behind the solution."

More Databricks pricing and cost advice

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"The solution must improve its licensing models."

"This solution is for large corporations because not everybody can afford it."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

27%

University

10%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 ...

See all answers

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...

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

What is your experience regarding pricing and costs for SAS Enterprise Miner?

The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pric...

See all answers

What needs improvement with SAS Enterprise Miner?

The product must provide better integration with cloud-native technologies.

See all answers

Comparisons

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Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau vs Databricks

Compared 5% of the time

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Compared 25% of the time

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Compared 21% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 19% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 19% of the time

TIBCO Data Science vs SAS Enterprise Miner

Compared 8% of the time

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Product Reports

Buyer's Guide

Databricks

July 2025

Download Databricks product report

Buyer's Guide

Data Mining

June 2025

Download SAS Enterprise Miner product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Enterprise Miner

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Databricks

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

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

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Databricks vs. SAS Enterprise Miner

June 2025

Free Report: Databricks vs. SAS Enterprise Miner

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