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Big Data on Tap™ with Release of SQLstream s-Server 3.0

SQLstream Inc. (www.sqlstream.com), a pioneer of real-time Big Data, today delivered the new generation of its streaming Big Data management platform. SQLstream s-Server 3.0 is the fastest and most scalable release of the company’s flagship product, introducing high performance distributed stream processing, Google BigQuery integration, and enhanced platform manageability and streaming application development.

SQLstream’s Big Data on Tap™ platform architecture is built from the ground up for real-time, streaming Big Data applications. The new release, with its real-time data collection, transformation and sharing capabilities, enables businesses to respond even faster to their operational Big Data. SQLstream s-Server 3.0 queries log file, sensor and service data in real-time, joins and transforms data streams using only the standard SQL language, and shares results continuously to outputs such as Big Data storage platforms. Streaming SQL enables high volume, high velocity applications for both structured and unstructured data to be built rapidly without having to resort to low level code development.

With s-Server 3.0, throughput performance is up to 10 times faster than that of the previous releases. The performance breakthrough is enabled by lock-free distributed processing for live data streams, a method pioneered by SQLstream and essential for real-time Big Data scalability. In addition, s-Server 3.0 brings faster integration, achieved through a new bi-directional connector for Google BigQuery, and faster development through new streaming SQL operators and added Windows support.

“Recent EMA research shows that Big Data environments consist of multiple platforms including structured (RDBMS) and multi-structured (Hadoop and other NoSQL) data stores – each one handling the processing that matches the strengths of the platform. This collection is called the Hybrid Data Ecosystem,” said John Myers, senior business intelligence and data warehousing analyst at Enterprise Management Associates. “Streaming Big Data solutions like SQLstream s-Server offer continuous integration with real-time analysis. This will be important in the area of operational intelligence analysis where low query latency is key.”

“SQLstream s-Server 3.0 addresses the operational Big Data problems that other log and network monitoring software solutions are unable to solve,” said Damian Black, SQLstream CEO. “Organizations want to be more responsive to their real-time Big Data, and that requires low latency and raw performance, plus our ability to join and share data continuously between any data source and any destination storage platform.”

An early availability program for SQLstream s-Server 3.0 validated the new performance and integration capabilities across a range of industries including telecommunications, transportation, financial services and High Performance Computing (HPC). High performance log file and machine data processing was a key requirement, met by SQLstream s-Server 3.0’s ability to detect operational issues in high volume, high velocity data streams that were out of range for existing log monitoring systems.

“We had too many systems producing too many logs too quickly for any of our existing tools to process in real-time or otherwise,” says Lucia Walle, Cornell University Center for Advanced Computing. “SQLstream is the solution that scaled to monitor logs in real time for key patterns indicating imminent and undesirable conditions.”

To download a free trial and for more information about SQLstream s-Server 3.0, its technical capabilities, business benefits, and our Big Data on Tap™ approach, visit www.sqlstream.com/whats-new-in-3.

About SQLstream Inc.

SQLstream Inc. (www.sqlstream.com) makes systems responsive to real-time operational Big Data. SQLstream enables organizations to query their log, sensor and service data directly, and to share streaming operational intelligence with external systems, continuously and in real-time. SQLstream is built on a standards-based, distributed and massively parallel architecture, and uses industry standard SQL for the rapid analysis of high volume, real-time data streams. Standards mean lower costs, proven performance and seamless integration. SQLstream is headquartered in San Francisco, CA.

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