Databricks Data Intelligence Platform vs. SAS Enterprise Guide

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Data Intelligence Platform
Score 8.4 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 Guide
Score 9.6 out of 10
N/A
SAS Enterprise Guide is a menu-driven, Windows GUI tool for SAS.N/A
Pricing
Databricks Data Intelligence PlatformSAS Enterprise Guide
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 Data Intelligence PlatformSAS Enterprise Guide
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 Data Intelligence PlatformSAS Enterprise Guide
Top Pros
Top Cons
Best Alternatives
Databricks Data Intelligence PlatformSAS Enterprise Guide
Small Businesses

No answers on this topic

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Score 7.8 out of 10
Medium-sized Companies
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Score 9.0 out of 10
Alteryx
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Score 9.0 out of 10
Enterprises
Snowflake
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Score 9.0 out of 10
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Score 7.8 out of 10
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User Ratings
Databricks Data Intelligence PlatformSAS Enterprise Guide
Likelihood to Recommend
8.4
(17 ratings)
5.3
(9 ratings)
Likelihood to Renew
-
(0 ratings)
8.0
(1 ratings)
Usability
9.5
(3 ratings)
5.0
(2 ratings)
Support Rating
8.6
(2 ratings)
5.3
(5 ratings)
Implementation Rating
-
(0 ratings)
7.0
(1 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Data Intelligence PlatformSAS Enterprise Guide
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 Guide is good at taking various datasets and giving analyst/user ability to do some transformations without substantial amounts of code. Once the data is inside SAS, the memory of it is very efficient. Using SAS for data analysis can be helpful. It will give good statistics for you, and it has a robust set of functions that aid analysis.
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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
  • I think the most useful aspect of SAS Enterprise Guide is the ability to use a point-and-click interface to create graphics, transform data, and perform statistics. The best part is that SAS Enterprise Guide creates base SAS code from the process, making it easy to reproduce analyses.
  • SAS Enterprise Guide makes creating summary statistics about as easy as it gets. If one doesn't know proc means or proc tabulate, one can use SAS Enterprise Guide instead.
  • The time-series forecasting procedures within SAS Enterprise Guide produce fairly good results. SAS Enterprise Guide makes time-series model comparisons relatively straight-forward.
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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
  • SAS Studio has some great examples that can be implemented. Adding a filter to the output datasets for one.
  • Some issues around having to enter my password every time I open it up. Some people are having this issue and others aren't. SAS admin is at a loss to work out why it's occurring.
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Likelihood to Renew
Databricks
No answers on this topic
SAS
On account of current user experience and the organization-wide acceptance.
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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
It's not all bad, but I don't believe that an enterprise purchase of SAS is worth the expense considering the widely available set of tools in the data analytics space at the moment. In my company, it's a good tool because others use it. Otherwise, I wouldn't purchase a new set of it because it doesn't have some of the better analytical functions in it.
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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 did not use the technical support of SAS EG. I can say that I have had hard time to find online tutorials or projects for SAS EG. For instance, it is hard to find completed researches or designed algorithms used with SAS EG. Sometimes it just depends on user's skill set and experience with databases and programming.
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Implementation Rating
Databricks
No answers on this topic
SAS
I've not worked hands-on with the implementation team, but there were no escalations barring a few hiccups in the deployment due to change in requirement & adoption to our company's remote servers.
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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
Why I prefer SAS EG: Data processing speed is much faster than that R Studio. It can load any amount of data and any type of data like structured or unstructured or semi-structured. Its output delivery system by which we have the output in PDF file makes it very comfortable to use and share that file to clients very easily. Inbuilt functions are very powerful and plentiful. Facility of writing macros makes it far away from its competitors.
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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
  • Positive (cost): SAS made a bundle that include unlimited usage of SAS/Enterprise Guide with a server solution. That by itself made the company save a lot of money by not having to pay individual licences anymore.
  • Positive (insight): Data analysts in business units often need to crunch data and they don't have access to ETL tools to do it. Having access to SAS/EG gives them that power.
  • Positive (time to market): Having the users develop components with SAS/EG allows for easier integration in a production environment (SAS batch job) as no code rework is required.
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