Real-time streaming data ingestion is a common application requirement. In industries like IoT, e-commerce, communications, entertainment, finance, and retail, where so much depends on timely and accurate data-driven decision making, real-time data collection and analysis are core to the business. However, collecting, storing, and processing streaming data in large volumes and at high velocity can present significant architectural challenges. Redis has become a popular choice for such fast data ingest scenarios. A lightweight in-memory database platform, Redis achieves throughput in the millions of operations per second with sub-millisecond latencies, while drawing on minimal resources. It also offers simple implementations, enabled by its multiple data structures and functions.
In this session, we'll cover how Redis Enterprise can solve common challenges associated with the ingestion and processing of large volumes of high-velocity data. We’ll walk through three different approaches (including code) to processing a Twitter feed in real time, using Redis Pub/Sub, Redis Lists, and Redis Sorted Sets.