What users are saying about

Apache Spark<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>Customer Verified: Read more.</a>

97 Ratings

Apache Spark<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>Customer Verified: Read more.</a>

97 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 8.6 out of 101

SAS Visual Analytics

40 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 7.8 out of 101

Add comparison

Likelihood to Recommend

Apache Spark

Spark is great as a workflow process and extract transform layer process tool. Is really good for machine learning especially for large datasets that can be processed in split file paralallelization. Spark streaming is scalable for close to real-time data workflow process.what it's not good for, is smaller subset of data processing.
Anson Abraham profile photo

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!
Ian Macintosh profile photo

Feature Rating Comparison

BI Standard Reporting

Apache Spark
SAS Visual Analytics
7.0
Pixel Perfect reports
Apache Spark
SAS Visual Analytics
7.2
Customizable dashboards
Apache Spark
SAS Visual Analytics
7.5
Report Formatting Templates
Apache Spark
SAS Visual Analytics
6.3

Ad-hoc Reporting

Apache Spark
SAS Visual Analytics
8.3
Drill-down analysis
Apache Spark
SAS Visual Analytics
8.9
Formatting capabilities
Apache Spark
SAS Visual Analytics
9.0
Integration with R or other statistical packages
Apache Spark
SAS Visual Analytics
8.5
Report sharing and collaboration
Apache Spark
SAS Visual Analytics
7.0

Report Output and Scheduling

Apache Spark
SAS Visual Analytics
8.4
Publish to Web
Apache Spark
SAS Visual Analytics
8.1
Publish to PDF
Apache Spark
SAS Visual Analytics
7.6
Report Versioning
Apache Spark
SAS Visual Analytics
8.5
Report Delivery Scheduling
Apache Spark
SAS Visual Analytics
8.8
Delivery to Remote Servers
Apache Spark
SAS Visual Analytics
8.9

Data Discovery and Visualization

Apache Spark
SAS Visual Analytics
8.4
Pre-built visualization formats (heatmaps, scatter plots etc.)
Apache Spark
SAS Visual Analytics
9.0
Location Analytics / Geographic Visualization
Apache Spark
SAS Visual Analytics
8.0
Predictive Analytics
Apache Spark
SAS Visual Analytics
8.3

Access Control and Security

Apache Spark
SAS Visual Analytics
7.6
Multi-User Support (named login)
Apache Spark
SAS Visual Analytics
7.6
Role-Based Security Model
Apache Spark
SAS Visual Analytics
8.1
Multiple Access Permission Levels (Create, Read, Delete)
Apache Spark
SAS Visual Analytics
7.2
Single Sign-On (SSO)
Apache Spark
SAS Visual Analytics
7.7

Mobile Capabilities

Apache Spark
SAS Visual Analytics
8.4
Responsive Design for Web Access
Apache Spark
SAS Visual Analytics
7.8
Dedicated iOS Application
Apache Spark
SAS Visual Analytics
8.2
Dedicated Android Application
Apache Spark
SAS Visual Analytics
8.6
Dashboard / Report / Visualization Interactivity on Mobile
Apache Spark
SAS Visual Analytics
9.0

Application Program Interfaces (APIs) / Embedding

Apache Spark
SAS Visual Analytics
8.0
REST API
Apache Spark
SAS Visual Analytics
8.2
Javascript API
Apache Spark
SAS Visual Analytics
8.2
iFrames
Apache Spark
SAS Visual Analytics
8.2
Java API
Apache Spark
SAS Visual Analytics
8.2
Themeable User Interface (UI)
Apache Spark
SAS Visual Analytics
7.1
Customizable Platform (Open Source)
Apache Spark
SAS Visual Analytics
8.2

Pros

  • It performs a conventional disk-based process when the data sets are too large to fit into memory, which is very useful because, regardless of the size of the data, it is always possible to store them.
  • It has great speed and ability to join multiple types of databases and run different types of analysis applications. This functionality is super useful as it reduces work times
  • Apache Spark uses the data storage model of Hadoop and can be integrated with other big data frameworks such as HBase, MongoDB, and Cassandra. This is very useful because it is compatible with multiple frameworks that the company has, and thus allows us to unify all the processes.
Carla Borges profile photo
  • Stock market analysis.
  • Resource utilization and optimization.
  • Pivot table analysis.
Banbhalang Kharpuri profile photo

Cons

  • Data visualization.
  • Waiting for Web Development for small apps to be started with Spark as backbone middleware and HDFS as data retrieval file system.
  • Transformations and actions available are limited so must modify API to work for more features.
Kamesh Emani profile photo
  • Support. Have had billing and license/key issues. The first time my staff reached out to support, they recommended contacting our site admin for help (me). If we could help ourselves, why would we contact? Support seems lacking.
  • Download. The install file is huge and can be an issue for remote employees, or areas where networking is poor.
Mike Narumiya 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

Apache Pig and Apache Hive provide most of the things spark provide but apache spark has more features like actions and transformations which are easy to code. Spark uses optimization technique as we can select driver program and manipulate DAG (Directed Acyclic Graph)Python can be used even for data transformations but it requires lot of coding compared to Spark and it is even so slow.
Kamesh Emani profile photo
Price and features we looked at seemed consistent. We chose this product because our staff already knew the product, plus users at the state had recommended it as it is what they use.
Mike Narumiya profile photo

Collaboration and Sharing

No score
No answers yet
No answers on this topic
SAS Visual Analytics6.7
Based on 6 answers
Users can access it without login information as seen with the University of Texas at Dallas public Dashboard*. It also provides administrators to provide user role based privileges to display the modification of a report.* All data, charts and copyright for the above charts above belong to University of Texas System
No photo available

Data Integration

No score
No answers yet
No answers on this topic
SAS Visual Analytics7.7
Based on 6 answers
Data builder provides options to merge multiple data tables through a GUI tool. It does not require a user to have coding experience to perform this operation.
No photo available

Return on Investment

  • Positive: we don't worry about scale.
  • Positive: large support community.
  • Negative: Takes time to set up, overkill for many simpler workflows.
No photo available
  • 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.