Streaming SQL databases can simplify how organizations work with streaming data sources like Apache Kafka. A complete SQL streaming database provides the powerful offering to developers of asking questions about streaming data, and then getting correct answers with millisecond latency, even when the underlying data changes rapidly - commonly called incremental view maintenance.
Data engineers build applications in streaming SQL databases using ANSI-standard SQL, so there is no need to develop custom code which significantly reduces costs and time-to-market.
In this presentation, Materialize Chief Scientist Frank McSherry will review the architectural details that distinguish how streaming SQL databases differ from traditional systems, demonstrate streaming data exploration using standard SQL, and showcase interactive, incrementally-maintained queries over continually-changing data sets. Materialize is based on Timely Dataflow and Differential Dataflow, providing a complete streaming SQL database solution with support for complex, multi-way JOINs on streaming data.