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 #23. Databricks holds a 8.3% mindshare in Data Science Platforms, compared to SAS’s 1.8% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Databricks

Read 93 Databricks reviews

19,983 Views
8,393 Comparison Views

96% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,532 Views
1,195 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: April 2026).

Buyer's Guide

Databricks vs. SAS Enterprise Miner

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

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 (4th), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)

SAS Enterprise Miner

Ranking in Data Science Platforms

23rd

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of April 2026, in the Data Science Platforms category, the mindshare of Databricks is 8.3%, down from 18.2% compared to the previous year. The mindshare of SAS Enterprise Miner is 1.8%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Databricks	8.3%
SAS Enterprise Miner	1.8%
Other	89.9%

Data Science Platforms

Featured Reviews

SimonRobinson

Governance And Engagement Lead

Improved data governance has enabled sensitive data tracking but cost management still needs work

I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.

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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

"Our company makes comprehensive use of the solution to consolidate data and do a certain amount of reporting and analytics."

"The solution offers a free community version."

"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."

"Databricks' Lakehouse architecture has been most useful for us, and the data governance has been absolutely efficient in between other kinds of solutions."

"Data is open to everyone; they can access it through many channels, including notebooks or SQL."

"It's great technology."

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

"We looked at both Snowflake and BigQuery as a comparison with this solution, and we chose this product as it offered more scalability and a higher level of security, which is extremely important in our banking environment."

More Databricks pros

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

"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."

"It enables statistical modeling of data using Base SAS (another product from the same vendor) as the backbone."

"SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help."

"I found the ease of use of the solution the most valuable."

"he solution is scalable."

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

More SAS Enterprise Miner pros

Cons

"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

"CI/CD needs additional leverage and support."

"We'd like a more visual dashboard for analysis It needs better UI."

"Databricks could improve in some of its functionality."

"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"This is a fairly expensive solution for any service outside of the basic package, and costs can add up quite quickly if there are large scaling requirements."

"CI/CD needs additional leverage and support."

More Databricks cons

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

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

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

"Price of the product"

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

"The license is really expensive. This solution is for large corporations because not everybody can afford it."

More SAS Enterprise Miner cons

Pricing and Cost Advice

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

"The solution requires a subscription."

"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."

"The pricing depends on the usage itself."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

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

"The product pricing is moderate."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

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

18%

Manufacturing Company

Computer Software Company

Healthcare Company

Financial Services Firm

18%

Construction Company

12%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	27
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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Product Reports

Buyer's Guide

Databricks

April 2026

Download Databricks product report

Buyer's Guide

Data Mining

March 2026

Download SAS Enterprise Miner product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Enterprise Miner

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

SAS Enterprise Miner enables comprehensive data management and analytics, handling extensive data volumes with diverse algorithms for model creation. Its integration and flexibility in SAS code usage make it suitable for both enterprise and personal use.

SAS Enterprise Miner is recognized for its data pipeline visualization, data processing, and statistical modeling capabilities. Its user-friendly GUI and automation support data mining tasks, decision tree creation, and clustering. However, improvements are needed in its interface visualization, affordability, technical support, and integration with languages like Python and cloud-native tech. Enhanced performance, visualization, and model development auditing, along with text analytics in the main license, are desirable upgrades. Integration with Microsoft SQL and combined offerings remains a priority.

What are SAS Enterprise Miner's most important features?

Data Management: Handles large data volumes efficiently.
Analytics: Integrates diverse algorithms for accurate model creation.
Integration: Supports flexible incorporation of SAS code.
Automation: Enhances data mining tasks through automation.
Clustering: Facilitates extensive clustering operations.

What benefits or ROI should users look for in reviews?

Performance: Delivers remarkable efficiency in data processing tasks.
Compatibility: Seamless integration with other technologies.
Flexibility: Adaptability for enterprise and personal use cases.
User-Friendly: Intuitive GUI aids in simplifying complex tasks.

SAS Enterprise Miner is applied across industries like banking, insurance, and healthcare for data mining, machine learning, and predictive analytics. It aids in activities such as text mining, fraud modeling, and forecasting model creation, handling structured and unstructured data, and performing ad hoc analysis to model business processes and analyze data clusters.

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

April 2026

Free Report: Databricks vs. SAS Enterprise Miner

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