We performed a comparison between Databricks and SAS Visual Analytics based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The technical support is good."
"The ability to stream data and the windowing feature are valuable."
"It's great technology."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"Databricks helps crunch petabytes of data in a very short period of time."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"It's a stable, reliable product."
"It provided the capability to visualize a bunch of data in an organized way."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"I use Visual Analytics for enterprise reporting."
"It's relatively simple to create basic dashboards and reports."
"It integrates well with SAS, making it simple and quick for developers."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"Great for handling complex data models."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"Doesn't provide a lot of credits or trial options."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"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."
"Databricks can improve by making the documentation better."
"There should be better integration with other platforms."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"The licensing ends up being more expensive than other options."
"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."
"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."
"I haven't come across any missing features."
"There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else."
"The solution is a little weak at the front end."
"The installation process can be a bit complex."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.
Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.
Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.
Databricks Key Features
Some of Databricks key features include:
Reviews from Real Users
Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.
PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”
A business intelligence coordinator in construction notes, “The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.”
An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”
SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.
SAS Visual Analytics Features
SAS Visual Analytics has many valuable key features. Some of the most useful ones include:
SAS Visual Analytics Benefits
There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.
A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.
PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.
Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”
Databricks is ranked 1st in Data Science Platforms with 35 reviews while SAS Visual Analytics is ranked 4th in Data Visualization with 13 reviews. Databricks is rated 8.2, while SAS Visual Analytics is rated 8.4. The top reviewer of Databricks writes "Good integration with majority of data sources through Databricks Notebooks using Python, Scala, SQL, R". On the other hand, the top reviewer of SAS Visual Analytics writes "Easy to learn and use with good scalability potential". Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Dataiku Data Science Studio, Azure Stream Analytics and Oracle Analytics Cloud, whereas SAS Visual Analytics is most compared with Tableau, Microsoft BI, Qlik Sense, Dataiku Data Science Studio and Microsoft Azure Machine Learning Studio.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.