The core idea of the lambda architecture is that incoming data should be recorded by appending immutable events to an always-growing dataset, similarly to event sourcing (see “Event Sourcing”). From these events, read-optimized views are derived. The lambda architecture proposes running two different systems in parallel: a batch processing system such as Hadoop MapReduce, and a separate stream-processing system such as Storm.
