No more typing reviews! Try our Samantha, our new voice AI agent.

Databricks vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
93
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
13
Ranking in other categories
Data Mining (7th)
 

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Databricks is 8.2%, down from 17.2% compared to the previous year. The mindshare of SAS Enterprise Miner is 2.1%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Databricks8.2%
SAS Enterprise Miner2.1%
Other89.7%
Data Science Platforms
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
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.
reviewer1352853 - PeerSpot reviewer
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…

Quotes from Members

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

Pros

"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"We recommend Databricks, especially with the Azure cloud frameworks."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"Prior to using Azure Databricks in the cloud, we had Databricks installed in clusters, and since our implementation, the performance has increased and our cost has been reduced."
"It's great technology."
"We can scale the product."
"One of the newest features brought into this solution provides you with a way to solve, deploy, and train models using the platform itself, or it can connect to your Azure Machine Learning in order to train, deploy, and productionalize some of the machine learning models."
"It enables statistical modeling of data using Base SAS (another product from the same vendor) as the backbone."
"Overall it is a good solution."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The data processing of the solution is very good, easy to use, both for enterprise and personal use."
"The technical support is very good."
"The solution is able to handle quite large amounts of data beautifully."
"he solution is scalable."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
 

Cons

"It should have more compatible and more advanced visualization and machine learning libraries."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"The integration of data could be a bit better."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The tool should improve its integration with other products."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"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."
"The license is really expensive. This solution is for large corporations because not everybody can afford it."
"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 preparation of both the mining and modeling process could be improved. The solution requires data and will reflect data, but the preparation of the data is not useful for end-users; we ended up having to do the preparation in another tool."
"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."
"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."
"Price of the product"
 

Pricing and Cost Advice

"We only pay for the Azure compute behind the solution."
"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 price of Databricks is reasonable compared to other solutions."
"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."
"The solution is a good value for batch processing and huge workloads."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."
"The product pricing is moderate."
"The solution must improve its licensing models."
"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."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
894,830 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
17%
Manufacturing Company
9%
Computer Software Company
7%
Healthcare Company
6%
Financial Services Firm
18%
Construction Company
12%
Educational Organization
9%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise57
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise4
Large Enterprise7
 

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 ...
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...
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...
Ask a question
Earn 20 points
 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Enterprise Miner
 

Overview

 

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
Find out what your peers are saying about Databricks vs. SAS Enterprise Miner and other solutions. Updated: April 2026.
894,830 professionals have used our research since 2012.