SQLstream Proves 15x Faster with Lower Total Cost of Ownership in Streaming Big Data Performance Test

SQLstream s-Streaming Big Data Engine Benchmarks at 1.35 Million Streaming Events Per Second per 4-core server  – Outperforming Twitter’s Storm Stream Computation Project with Significant Overall TCO Advantage. New York, NY | March 20, 2013– SQLstream Inc., the Streaming Big Data Company, announced today at GigaOM’s Structure:Data, the results of an independent performance benchmark which measured the SQLstream s-Server 3.0 Big Data Engine processing 1.35 million 1Kbyte records per second per 4-core commodity server, outperforming a comparable configuration based on the Twitter Storm distributed real-time computation system. SQLstream’s s-Server outperformed the Storm-based solution by a factor of 15x.

SQLstream’s s-Streaming Big Data Engine delivers action-oriented analytics, extracting operational intelligence in real-time from high velocity, unstructured log file, sensor and other machine-generated data. Streaming intelligence can be persisted, queried and replayed in Hadoop, with additional connectors to all major storage platforms and data warehouses.

The streaming Big Data benchmark was conducted by a large enterprise with a roadmap to stream unstructured operational data from multiple remote log and machine data flows at up to 10 million records per second for each installation. The benchmark requirement was to perform advanced time-series analytics over mobile network infrastructure records in order to predict potential service-impact problems. The benchmark projects that the s-Server platform would require just eight servers to scale up to 10 million records per second — versus an estimated more than 110 servers for the comparable Storm approach.

SQLstream s-Server 3.0 was able to demonstrate significant cost savings with dramatically lower TCO. The TCO savings came from a combination of reduced hardware and power consumption, the power and simplicity of SQL over low-level Java development, plus reduced maintenance requirements. Other factors influencing SQLstream s-Server’s TCO advantage came from its integrated Big Data platform architecture, ability to update on the fly as new data flows are incorporated, significantly faster implementation timescales using SQL for streaming analytics and integration, and automatic platform optimization for turbo-charged performance and parallel dataflow execution.

“SQLstream excels through the combination of its mature, industry-strength streaming Big Data platform, our support for standard SQL (SQL:2008) for streaming analysis and integration, plus a flexible adapter and agent architecture,” said SQLstream CEO Damian Black. “SQLstream s-Server is today’s clear streaming performance winner – with blazingly fast throughput, an ability to handle a wide variety of message types, sources and formats, and an efficient Streaming Data Protocol with compact optimized binary data formats.”

Advantages of SQLstream’s s-Server, the core element of the company’s s-Streaming Big Data Engine, as demonstrated in the performance benchmark project include:

  • Scaling to a throughput of 1.35 million 1Kbyte records per second per four-core server each fed by twenty remote streaming agents.
  • Expressiveness of the standards-based streaming SQL language with support for enhanced streaming User Defined Functions and User Defined Extensions (UDF/UDX).
  • Deploying new processing analytics pipelines on the fly without having to stop and recompile or rebuild applications.
  • Advanced pipeline operations including data enrichment, sliding time windows, external data storage platform read and write, and other advanced time-series analytics, all based on existing SQL standards.
  • Advanced memory management, with query optimization and execution environments to utilize and recover memory efficiently.
  • Higher throughput and performance per server for lower hardware requirements, lower costs and simple to maintain installations.
  • Proven and mature enterprise-grade product with a validated roadmap and controlled release schedule.

All required modules used in the benchmark were integrated with s-Server 3.0, using 20 remote streaming agents connected per SQLstream s-Server instance each running on a four-core Intel® Xeon© server platform with RedHat Enterprise Linux.

About SQLstream

SQLstream (www.sqlstream.com) is the pioneer and innovator of a patented Streaming Big Data Engine that unlocks the real-time value of high-velocity unstructured machine data. SQLstream’s
s-Streaming products put “Big Data on Tap™ – enabling businesses to harness action-oriented and predictive analytics, with on the fly visualization and streaming operational intelligence from their log file, sensor, network and device data. SQLstream’s core V5 streaming technology is a massively scalable, distributed platform for analyzing unstructured Big Data streams using standards-based SQL, with support for streaming SQL query execution over Hadoop/HBase, Oracle, IBM, and other enterprise database, data warehouse and data management systems.  SQLstream’s headquarters are in San Francisco, CA.