SQLstream’s Stream Processor brings real-time streaming SQL analytics for machine data to Apache Storm.
SAN FRANCISCO, CA – 11 February 2014 – SQLstream, Inc., the Big Data Stream Processors company, today announced the availability of its Stream Processor for Apache Storm, the open source distributed stream computing framework. The release enables the real-time analysis of machine data in Storm using continuous SQL queries. Organizations benefit from the improved performance, operational flexibility and reduced management costs of using standards-compliant SQL for the real-time analysis and integration of streaming data.
Storm is a distributed stream-processing framework available under the Apache Open Source license. The primary focus of the Storm project is its distributed infrastructure, rather than the real-time analytics or connectors for machine data sources and enterprise storage platforms. That is where SQLstream comes in. SQLstream’s Stream Processor for Storm enables Storm implementations to utilize continuous SQL queries for streaming analytics.
“We are proud to enhance Storm with SQLstream’s capabilities,” said Damian Black, SQLstream CEO. “Now Storm users can benefit from the analytic power of continuous SQL queries and will also enjoy an order of magnitude improvement both in stream processing performance and in reduction of hardware costs over standalone Storm implementations.”
SQLstream’s Stream Processor for Storm enables SQLstream s-Server continuous SQL queries to be deployed as Storm Bolts (stream processing nodes) in a distributed Storm system. SQLstream’s s-Server stream processor can also be deployed as Storm Spouts (machine data sources), utilizing SQLstream’s agents and adapters for real-time machine data collection and integration.
Organizations with an existing Storm deployment, or considering a future Storm implementation, will benefit from:
- Greater performance throughput on significantly less hardware. Benchmarks indicate that SQLstream’s Stream Processors on Storm deployments can achieve a 10x reduction in hardware for the same processing throughput performance.
- Faster time to value for real-time applications. Storm Bolts can now be written as declarative continuous standards-compliant SQL queries. Real-time analytics and continuous integration applications can be deployed in a fraction of the time required to develop low level Java Bolts for example.
- Dynamic updates to operational Storm systems. Unlike a Storm-only implementation, Spouts and Bolts implemented using continuous SQL queries can be updated and changed dynamically without having to stop, rebuild and redeploy the Storm topology.
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The SQLstream API for Apache Storm is included in the latest SQLstream s-Server 4.0. For more information on SQLstream’s Stream Processor for Storm, visit http://www.sqlstream.com/storm, and to download a free trial of SQLstream s-Server 4.0, visit http://www.sqlstream.com/downloads.
SQLstream’s Stream Processors automate business processes using real-time analytics from unstructured sensor, log, and other machine-generated Big Data streams. SQLstream’s core stream processing engine, SQLstream s-Server, is a distributed, streaming SQL platform for real-time operational intelligence applications. SQLstream offers a full range of machine data integration agents plus integration with Hadoop and other enterprise data management platforms. SQLstream is the recipient of leading industry awards, including the Ventana Research Technology Innovation Award for IT Analytics and Performance. SQLstream is based in San Francisco, CA.