Databricks Lakehouse Platform vs. SAS Enterprise Miner

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Lakehouse Platform
Score 8.1 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
SAS Enterprise Miner
Score 8.7 out of 10
N/A
SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.N/A
Pricing
Databricks Lakehouse PlatformSAS Enterprise Miner
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
No answers on this topic
Offerings
Pricing Offerings
Databricks Lakehouse PlatformSAS Enterprise Miner
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Databricks Lakehouse PlatformSAS Enterprise Miner
Top Pros
Top Cons
Features
Databricks Lakehouse PlatformSAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
SAS Enterprise Miner
8.8
5 Ratings
4% above category average
Connect to Multiple Data Sources00 Ratings8.15 Ratings
Extend Existing Data Sources00 Ratings9.05 Ratings
Automatic Data Format Detection00 Ratings9.35 Ratings
MDM Integration00 Ratings9.03 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
SAS Enterprise Miner
8.1
5 Ratings
4% below category average
Visualization00 Ratings7.15 Ratings
Interactive Data Analysis00 Ratings9.25 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
SAS Enterprise Miner
8.0
5 Ratings
3% below category average
Interactive Data Cleaning and Enrichment00 Ratings7.85 Ratings
Data Transformations00 Ratings8.25 Ratings
Data Encryption00 Ratings8.13 Ratings
Built-in Processors00 Ratings8.13 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
SAS Enterprise Miner
8.8
5 Ratings
4% above category average
Multiple Model Development Languages and Tools00 Ratings7.55 Ratings
Automated Machine Learning00 Ratings9.93 Ratings
Single platform for multiple model development00 Ratings8.65 Ratings
Self-Service Model Delivery00 Ratings9.24 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
SAS Enterprise Miner
7.8
5 Ratings
9% below category average
Flexible Model Publishing Options00 Ratings7.05 Ratings
Security, Governance, and Cost Controls00 Ratings8.55 Ratings
Best Alternatives
Databricks Lakehouse PlatformSAS Enterprise Miner
Small Businesses

No answers on this topic

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Score 9.1 out of 10
Medium-sized Companies
Snowflake
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Score 9.0 out of 10
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Mathematica
Score 8.3 out of 10
Enterprises
Snowflake
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Score 9.0 out of 10
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Score 9.0 out of 10
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User Ratings
Databricks Lakehouse PlatformSAS Enterprise Miner
Likelihood to Recommend
8.4
(17 ratings)
9.9
(5 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
8.6
(2 ratings)
10.0
(2 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Lakehouse PlatformSAS Enterprise Miner
Likelihood to Recommend
Databricks
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
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SAS
SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
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Pros
Databricks
  • Process raw data in One Lake (S3) env to relational tables and views
  • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
  • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
  • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
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SAS
  • Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
  • The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
  • The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
  • Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
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Cons
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
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SAS
  • With large data sets, SAS Enterprise Miner sometimes takes a long time to run. Sometimes you have to just leave your computer running while Enterprise Miner does its thing.
  • If you want complete control over the modeling framework, you have to take what Enterprise Miner does and customize it. SAS seems to be working hard on making things easier to customize, but it's not completely there yet.
  • The graphic capabilities of SAS Enterprise Miner leave a lot to be desired, especially in the era of self-service business intelligence software.
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Usability
Databricks
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
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SAS
No answers on this topic
Support Rating
Databricks
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
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SAS
I have contacted SAS twice in the past year and they have been super responsive both times. They solved my problem. I am also registered for an in-person class next month and they called today to tell me that it will be an online-only session. They apologized for the change and registered me for the online version. Super helpful!
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Alternatives Considered
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
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SAS
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
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Return on Investment
Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
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SAS
  • SAS Enterprise Miner is a positive ROI in the sense that it saves a ton of time coding.
  • SAS Enterprise Miner is a negative ROI in that it's expensive, and perhaps makes analysts brainless.
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ScreenShots