Software solutions, such as those for personalization, metering, IoT require processing of extremely large volumes of data in real time. High-speed data ingest and processing poses several challenges such as

1. Managing large volume of data sometimes arriving in bursts
2. Receiving data from multiple sources
3. Filtering, analyzing or forwarding data with different formats

Redis, the high-speed, open source in-memory database platform offers data structures and messaging services, that enable combining high-speed data ingest and real-time analytics. This session will cover the architectural and design challenges in accomplishing fast data ingest and real-time analytics, and in combining the both. The second half of the session will focus on performing a live demonstration of combining fast data ingest and real-time analytics on Redis using

1. Redis Pub/Sub – publish and subscribe messaging framework
2. Redis List data structure for message queueing and filtering
3. Time series data modeling using Redis Sorted Set and Pub/Sub

The demonstration will show how to perform real-time analytics with examples in filtering, classification, aggregation, and deduplication.