A streaming SQL query is a continuous, standing query that executes over streaming data. Data streams are processed using familiar SQL relational operators augmented to handle time sensitive data. Streaming queries are similar to database queries in how they analyze data; they differ by operating continuously on data as they arrive and by updating results in real-time.

Streaming SQL queries process dynamic, flowing data, in contrast to traditional RDBMSs, which process static, stored data with repeated single-shot queries. Streaming SQL is simple to configure using existing IT skills, dramatically reducing integration cost and complexity. Combining the intuitive power of SQL with this simplicity of configuration enables much faster implementation of business ideas, while retaining the scalability and investment protection important for business-critical systems.

By processing transactions continuously, streaming SQL directly addresses the real-time business needs for low latency, high volume, and rapid integration. Complex, time- sensitive transformations and analytics, operating continuously across multiple input data sources, are simple to configure and generate streaming-analytics answers as input data arrive. Sources can include any application inputs or outputs, or any of the data feeds processed or generated within an enterprise. Examples include financial trading data, internet clickstream data, sensor data, and exception events. SQL can process multiple input and output streams of data, for multiple publishers and subscribers.

The above post was written for SQLstream and was also republished by open source pioneer Julian Hyde. For more on streaming data, open source and OLAP, see http://julianhyde.blogspot.com/