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 18.2% mindshare in Data Science Platforms, compared to SAS’s 0.7% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Databricks

Read 88 Databricks reviews

14,742 Views
10,545 Comparison Views

96% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

616 Views
474 Comparison Views

93% willing to recommend

Databricks

SAS Enterprise Miner

Comparison Buyer's Guide

Download the report

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: March 2025).

Buyer's Guide

Databricks vs. SAS Enterprise Miner

March 2025

Download the complete report

Helped 845,406 peers since 2012

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 (7th), 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 April 2025, in the Data Science Platforms category, the mindshare of Databricks is 18.2%, down from 19.1% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.7%, down from 0.9% 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.

Read full review

reviewer1447110

Senior Systems Engineer at a financial services firm with 10,001+ employees

Good technical support but too complex and not open-source

We're using Enterprise Guide simultaneously with Enterprise Miner. From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like Anaconda. They offer good support and features. Anaconda also integrates well with Jupyter NET, which is important for us. Overall, on a scale from one to ten, I'd rate the solution at a five. If there were better protocols and wasn't as complex as it is, I'd rate it a bit higher.

Read full review

Quotes from Members

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

Pros

"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."

"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."

"The setup was straightforward."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

"The solution is an impressive tool for data migration and integration."

"The technical support is good."

"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."

"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."

More Databricks pros

"The technical support is very good."

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

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

"he solution is scalable."

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

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

"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."

"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."

More SAS Enterprise Miner pros

Cons

"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 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."

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."

"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."

"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."

"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."

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

"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."

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."

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

"Virtualization could be much better."

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

"Technical support could be improved."

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

"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 pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."

"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."

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

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"The solution is affordable."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"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."

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

More Databricks pricing and cost advice

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

"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."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

845,406 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

26%

University

12%

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

Dataiku vs Databricks

Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

SAS Visual Analytics vs SAS Enterprise Miner

Compared 34% of the time

KNIME vs SAS Enterprise Miner

Compared 25% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 24% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 17% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

Data Mining

March 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

March 2025

Free Report: Databricks vs. SAS Enterprise Miner

Find out what your peers are saying about Databricks vs. SAS Enterprise Miner and other solutions. Updated: March 2025.

DOWNLOAD NOW

845,406 professionals have used our research since 2012.

See our Databricks vs. SAS Enterprise Miner report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.