It’s one thing to collect a large amount user-generated data and process it. It’s another to ingest and store massive amounts of machine-generated data in real time. This session will focus on how machines and things are changing database requirements from the throughput and latency they require, to the sheer number of them, to their evolving data model, and the impact of location on network availability.
The problem with analyzing large volumes of data is latency. First, it takes time to load data. Next, it takes time to analyze it. The results are always out of date because there is always more data. The solution is to perform a continuous analysis of data in motion, or stream processing. In this session, we’ll evaluate two popular, open source stream processors, Spark and Storm, and discuss how they can be integrated with Couchbase Server as a streaming input source or as destination for the output.