We performed a comparison between Databricks and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The simplicity of development is the most valuable feature."
"Ability to work collaboratively without having to worry about the infrastructure."
"The time travel feature is the solution's most valuable aspect."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The setup was straightforward."
"It's very simple to use Databricks Apache Spark."
"It's relatively simple to create basic dashboards and reports."
"It's a stable, reliable product."
"The product is stable, reliable, and scalable."
"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools."
"We've found the product to be stable and reliable."
"The technical support services are good."
"The speed to display charts and react to users' choices is great."
"Data handling is one of the best features of SAS Visual Analytics."
"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."
"I would like more integration with SQL for using data in different workspaces."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"The initial setup is difficult."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"The installation process can be a bit complex."
"Colours used on report objects"
"I haven't come across any missing features."
"In Brazil, there are few documents, courses, and other resources for studying and implementing the tool."
"There is a need for coding when it comes to digital reporting which can be intimidating."
"SAS Visual Analytics could improve by making it more accessible for users outside the organization."
"SAS Visual Analytics could be more user-friendly."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 36 reviews. Databricks is rated 8.2, while SAS Visual Analytics is rated 8.2. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Oracle Analytics Cloud, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Microsoft Azure Machine Learning Studio, Dataiku and SAS Enterprise Miner.
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