Incremental data processing is a method of applying computations to a newly added data subset. It may drastically help decrease the cost and processing time in Big Data systems. However, this method may also increase complexity. This approach enables delivery of updates in real-time to the global-scale data receivers.

This talk takes a look at design choices and looks at how certain data structures or patterns, such as the Kappa architecture, can help build incremental data processing systems.