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EVENT DETAILS |
VIRTUAL-EVENT We will give away a whole bunch of free T-Shirts at this virtual-event!
Presented by Frank McSherry, Co-Founder & Chief Scientist, Materialize
REQUIRED to attend register now while there is still space:
http://rsvp.DBMonth.com
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, & 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 & 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, & showcase interactive, incrementally-maintained queries over continually-changing data sets. Materialize is based on Timely Dataflow & Differential Dataflow, providing a complete streaming SQL database solution with support for complex, multi-way JOINs on streaming data.
Frank McSherry, Co-Founder & Chief Scientist, Materialize
Frank McSherry is co-founder & Chief Scientist at Materialize (http://www.materialize.io)
Prior to starting Materialize, Frank co-invented Differential Privacy & led the Naiad project. Frank is the primary author of Timely Dataflow & Differential Dataflow, the two open source projects that power Materialize.
Frank previously worked at Microsoft Research Silicon Valley, & holds a Ph.D in Computer Science from the University of Washington.
Register now while there is still space:
http://rsvp.DBMonth.com
Virtual Power-Networking at 6:30pm
Freebie swag giveaway at 6:35pm
Presentation starts at 6:40pm
A Database Month event
http://www.DBMonth.com/database/streaming-sql
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