Sqlstream
| Initial release | 2009 |
|---|---|
| Type | Software |
| Website | www |
SQLstream is a distributed, SQL standards-compliant plus Java stream processing platform. SQLstream, Inc. is based in San Francisco, California and was launched in 2009 by Damian Black, Edan Kabatchnik and Julian Hyde, author of the open source Mondrian Relational OLAP Server Engine.
In 2016, SQLstream announced it had licensed a subset of SQLstream Blaze, its flagship product suite, to Amazon's AWS for their Kinesis Analytics service that provides streaming real-time insights and transformations for Amazon customers to Kinesis data streams. In the same year, Forrester had already published its Wave report on Streaming Analytics placing SQLstream in the Leadership Circle (their alternative to Gartner's Magic Quadrant). That year, SQLstream also announced that Kontron, the world's second largest embedded systems supplier, had standardized on SQLstream Blaze for its IoT data acquisition, analysis and real-time action and dashboarding. SQLstream was listed for the fourth year in a row in the DBTA 100 (Database Trends and Applications magazine) which is their list of the 100 companies that matter most in data. In the same year, they announced Rubicon, a publicly-traded company and a leader in real-time advertising, to provide real-time insights into massive volumes of data reducing latency from three hours with Hadoop to near real-time and reducing the number of servers required to perform such analytics from 180 servers to 12 servers.
The rapid increase in the volume of available service, device and sensor data has led to new, real-time market segments which augment the traditional monitoring, business intelligence and data warehousing domains. The Internet of Things promises to bring hundreds of billions of connected devices to the Internet, all streaming out data that need to be processed in aggregate in real-time in order to power smart services that can react and respond to their environment through these sensors. Stored data analytics systems where one continually updates the data store with newly arriving data and re-traverse the stored data in order to perform analysis on the data do not scale up to the very large volumes of data emitted in the Internet of Things. They are not designed for issuing queries or analyses for each of millions of records per second. This is where technologies like SQLstream come in, that process the data incrementally and continually, without first storing the data. Such an approach is called Stream Processing. All of this information was released in public press releases.
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