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 8.4, while SAS is ranked #24. Databricks holds a 13.9% mindshare in Data Science Platforms, compared to SAS’s 1.2% 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

20,775 Views
8,933 Comparison Views

96% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

833 Views
600 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: September 2025).

Buyer's Guide

Databricks vs. SAS Enterprise Miner

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)

SAS Enterprise Miner

Ranking in Data Science Platforms

24th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

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 SAS Enterprise Miner is 1.2%, up from 0.7% 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%
SAS Enterprise Miner	1.2%
Other	84.9%

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

"Databricks serves as a single platform that can handle numerous end-to-end machine learning tasks."

"Easy to use and requires minimal coding and customizations."

"Databricks' most valuable feature is the data transformation through PySpark."

"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."

"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."

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

"The fast data loading process and data storage capabilities are great."

"There are good features for turning off clusters."

More Databricks pros

"Good data management and analytics."

"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."

"he solution is scalable."

"The most valuable feature is the decision tree creation."

"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."

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

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

"The solution is able to handle quite large amounts of data beautifully."

More SAS Enterprise Miner pros

Cons

"The product cannot be integrated with a popular coding IDE."

"Implementation of Databricks is still very code heavy."

"The API deployment and model deployment are not easy on the Databricks side."

"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."

"The product should provide more advanced features in future releases."

"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"The Databricks cluster can be improved."

More Databricks cons

"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."

"Technical support could be improved."

"The initial setup is challenging if doing it for the first time."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

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

"Virtualization could be much better."

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

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

More SAS Enterprise Miner cons

Pricing and Cost Advice

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

"The solution is based on a licensing model."

"The cost is around $600,000 for 50 users."

"The solution is a good value for batch processing and huge workloads."

"The billing of Databricks can be difficult and should improve."

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

"There are different versions."

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

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."

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

"The solution must improve its licensing models."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

Manufacturing Company

Healthcare Company

Financial Services Firm

28%

Educational Organization

12%

University

11%

Manufacturing Company

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	3
Midsize Enterprise	4
Large Enterprise	7

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...

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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

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KNIME Business Hub vs SAS Enterprise Miner

Compared 33% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 14% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 12% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 11% of the time

TIBCO Data Science vs SAS Enterprise Miner

Compared 8% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

Data Mining

August 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

September 2025

Free Report: Databricks vs. SAS Enterprise Miner

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