Unifying Stream Processing with a Fast Data Store

In this session, we will describe an architecture that addresses simplicity and performance in stream processing deployments, while also reducing cost. This architecture aims for fewer moving parts, fewer clusters and servers to manage, fewer network hops, higher throughput, and lower latency, as well as less custom code.

We will demonstrate the combination of stream processing and fast data store in a unified real-time data platform. We will also discuss Streaming SQL features, Python and Java support, and best practices.

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