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102 Ratings
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Score 8.5 out of 101
41 Ratings
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Score 8.2 out of 101

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Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
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SAS Visual Analytics

It is particularly well suited to big data collections that have good structure. It is not really designed for unstructured datasets (documents, etc). Its strength is the processing speed (particularly when implemented on Hadoop). It is not cheap but it is worth it!
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Feature Rating Comparison

BI Standard Reporting

Apache Spark
SAS Visual Analytics
8.9
Pixel Perfect reports
Apache Spark
SAS Visual Analytics
9.0
Customizable dashboards
Apache Spark
SAS Visual Analytics
9.0
Report Formatting Templates
Apache Spark
SAS Visual Analytics
8.7

Ad-hoc Reporting

Apache Spark
SAS Visual Analytics
9.0
Drill-down analysis
Apache Spark
SAS Visual Analytics
9.4
Formatting capabilities
Apache Spark
SAS Visual Analytics
9.5
Integration with R or other statistical packages
Apache Spark
SAS Visual Analytics
9.0
Report sharing and collaboration
Apache Spark
SAS Visual Analytics
8.3

Report Output and Scheduling

Apache Spark
SAS Visual Analytics
9.1
Publish to Web
Apache Spark
SAS Visual Analytics
8.8
Publish to PDF
Apache Spark
SAS Visual Analytics
8.7
Report Versioning
Apache Spark
SAS Visual Analytics
9.2
Report Delivery Scheduling
Apache Spark
SAS Visual Analytics
9.4
Delivery to Remote Servers
Apache Spark
SAS Visual Analytics
9.4

Data Discovery and Visualization

Apache Spark
SAS Visual Analytics
9.4
Pre-built visualization formats (heatmaps, scatter plots etc.)
Apache Spark
SAS Visual Analytics
9.7
Location Analytics / Geographic Visualization
Apache Spark
SAS Visual Analytics
9.1
Predictive Analytics
Apache Spark
SAS Visual Analytics
9.4

Access Control and Security

Apache Spark
SAS Visual Analytics
8.5
Multi-User Support (named login)
Apache Spark
SAS Visual Analytics
8.7
Role-Based Security Model
Apache Spark
SAS Visual Analytics
8.7
Multiple Access Permission Levels (Create, Read, Delete)
Apache Spark
SAS Visual Analytics
8.1
Single Sign-On (SSO)
Apache Spark
SAS Visual Analytics
8.6

Mobile Capabilities

Apache Spark
SAS Visual Analytics
9.1
Responsive Design for Web Access
Apache Spark
SAS Visual Analytics
8.5
Dedicated iOS Application
Apache Spark
SAS Visual Analytics
9.2
Dedicated Android Application
Apache Spark
SAS Visual Analytics
9.2
Dashboard / Report / Visualization Interactivity on Mobile
Apache Spark
SAS Visual Analytics
9.5

Application Program Interfaces (APIs) / Embedding

Apache Spark
SAS Visual Analytics
9.1
REST API
Apache Spark
SAS Visual Analytics
9.2
Javascript API
Apache Spark
SAS Visual Analytics
9.2
iFrames
Apache Spark
SAS Visual Analytics
9.2
Java API
Apache Spark
SAS Visual Analytics
9.2
Themeable User Interface (UI)
Apache Spark
SAS Visual Analytics
8.4
Customizable Platform (Open Source)
Apache Spark
SAS Visual Analytics
9.2

Pros

  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
Nitin Pasumarthy profile photo
  • Visualization of large amount of data is faster because of the SAS engine behind it.
  • Features like decision trees, box plot, scatter plot, and histogram are very easy to use for exploring large data. It also has some unique features like Sankey Diagrams which can be used to show a flow of a process.
  • Customization options for the design of reports, making it visually more appealing.
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Cons

  • could do a better job for analytics dashboards to provide insights on a data stream and hence not have to rely on data visualization tools along with spark
  • also there is room for improvement in the area of data discovery
Shiv Shivakumar profile photo
  • More advanced dashboard features like multiple tabs creation.
  • Should have option to export dashboard reports to multiple formats with original format intact.
  • Latency time of reports and response should be increased.
suva sahu profile photo

Support

No score
No answers yet
No answers on this topic
SAS Visual Analytics10.0
Based on 1 answer
Excellent and fast support
suva sahu profile photo

Alternatives Considered

I prefer Apache Spark compared to Hadoop, since in my experience Spark has more usability and comes equipped with simple APIs for Scala, Python, Java and Spark SQL, as well as provides feedback in REPL format on the commands. At the same time, Apache Spark seems to have the best performance in the processing of large data that works in memory and, therefore, more processes can be downloaded on Spark than on Hadoop, despite the fact that Hadoop is also a very useful tool.
Carla Borges profile photo
SAS visual analytics has high sped LASR servers mounted on Hadoop filesystems which makes it more powrful for analytics.
suva sahu profile photo

Return on Investment

  • By learning Spark, we can become certified and/or provide proper recommendations or implementations on Spark solutions.
  • With a background in Hadoop distributed processes, it has been easy to understand and diagnose how Spark handles the transfer of data within a cluster. Especially when using YARN as the resource manager and HDFS as the data source.
  • Staying up to date with the latest changes to Spark has become a repetitive task. While most Hadoop distributions only support Spark 1.6 at the moment, Spark 2.0 has introduced some useful features, but those require a re-write of existing applications.
Jordan Moore profile photo
  • Expensive in dollars (but worth it)
  • Significant establishment effort but once set up easy to manage
  • good user feedback
Ian Macintosh profile photo

Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Apache Spark Editions & Modules
Apache Spark
Additional Pricing Details

SAS Visual Analytics

General
Free Trial
Yes
Free/Freemium Version
Premium Consulting/Integration Services
Yes
Entry-level set up fee?
No
SAS Visual Analytics Editions & Modules
SAS Visual Analytics
Edition
SAS Visual Analytics for SAS Cloud
1
1. Annual By Users: 5, 10, 20
Additional Pricing Details
SAS Visual Statistics and SAS Office Analytics are also available as add-ons.