In-Memory Visual Analytics
|Gartner selected Panopticon as a "Cool Vendor" in the Cool Vendors for In-Memory Computing 2013 report*. This is the first year that Gartner has called out In-Memory Computing specifically as a subject for one of its Cool Vendor reports. Learn more.|
When we first talk to customers, we show them our advanced data visualizations and how these can support visual analysis and monitoring based on their business requirements. This isn't surprising, of course, since visualizations like our interactive, real-time Treemaps and Heatmaps are the most obvious part of our visual data analysis software suite. However, information visualizations actually account for a very small part of our technology – in fact they form less than a tenth of the codebase in our platform.
Fast visual analysis of multi-dimensional data enabled by our StreamCube™ in-memory data model
Our unique StreamCube data model provides rich OLAP functionality that supports fast analysis through the visualizations. The data model can handle traditional multidimensional analysis for static data (like those specified by the MDX language) and also for dynamic data streams. In the case of dynamic data it lends itself to monitoring and analysis tasks across complex streaming problem sets within the financial services, utilities, telecoms, and corporate marketplaces.
In addition, the StreamCube enables Panopticon to connect directly to your data sources without requiring an expensive middle layer that adds unnecessary latency to your analytics system.
Many data models support multidimensional analytical OLAP functionality; however, most of them are not optimized for real-time performance. The Panopticon StreamCube is specifically designed to make extremely fast calculations using continuously updated data. The StreamCube matches the requirements that live visual interactive displays pose to a data back-end. This involves being able to bind aspects of the data to multiple visuals and associated analysis controls. Most other data models either cannot handle streaming data, or their performance degrades significantly when presented with large streaming feeds of real-time data.
StreamCube is unique:
- Supports multidimensional data
- Built for true high throughput real-time streaming data
- Supports static time series analysis (time cubes)
- Support for streaming time series analysis
- Handles aggregations & calculations
- Supports externally sourced aggregations
- Handles custom aggregation calculations
- Supports multiple in-memory independent cubes
- Supports shadow cubes that share common data dimensions
*Cool Vendors for In-Memory Computing 2013 report by Gartner, Inc. The April 23, 2013 report was co-authored by Roy Schulte, Roxane Edjlali, et al.
Gartner clients can access the full report here: http://www.gartner.com/resId=2447615
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.