SQLstream Introduces Visualization Platform for Streaming Analytics 

SQLstream Inc. announced today the world's first visualization dashboard product for streaming high-velocity data. SQLstream s-Visualizer provides active, graphical insights over real-time streaming analytics and is fully integrated with SQLstream's award-winning s-Server streaming Big Data platform.

SQLstream s-Visualizer is a drag-and-drop platform for building live dashboards over streaming data. Operational users rely on accurate, real-time information--yet traditional dashboard tools require data to be stored first, which introduces latency, and must be refreshed as new data arrive, which is unnecessarily resource-intensive. SQLstream s-Visualizer's dashboards are updated in real time, eliminating both: latency introduced by storing and aggregating data, and the resource overhead and inconvenience of constant refreshes, re-querying and polling.

"SQLstream s-Visualizer is the only product offering real-time immediate insight into fast data streams," said Damian Black, SQLstream CEO. "Users benefit from immediate insight into business issues and are empowered to quickly avert them."

Drinking from the fire hose of Big Data streams also poses a significant performance challenge for existing business intelligence and dashboard tools. Real-time operational intelligence applications must be able to process data at millions of records per second. SQLstream's intelligent on-the-fly aggregation and filtering of Big Data streams enables s-Visualizer to display meaningful analytics regardless of data volume and velocity.

SQLstream s-Visualizer offers:

• Access to streaming, real-time analytics on any platform - web, desktop and mobile devices;
• Full integration with SQLstream s-Server for display of streaming operational intelligence, plus support for combining streaming data with historical trend data from any existing storage platform or data;
• Customizable, metadata-driven interfaces for building personalized dashboards in minutes, with visual programming and drag-and-drop workflows.