Lambda+, the renewal of the Lambda Architecture: Category Theory to the rescue
Résumé
Designing software architectures for Big Data is a complex task that has to take into consideration multiple parameters, such as the expected functionalities, the properties that are untradeable, or the suitable technologies. Patterns are abstractions that guide the design of architectures to reach the requirements. One of the famous patterns is the Lambda Architecture, which proposes realtime computations with correctness and fault-tolerance guarantees. But the Lambda has also been highly criticized, mostly because of its complexity and because the real-time and correctness properties are each effective in a different layer but not in the overall architecture. Furthermore, its use cases are limited, whereas Big Data need an adaptive and flexible environment to fully reveal the value of data. Nevertheless, it proposes some interesting mechanisms. We present a renewal of the Lambda Architecture: the Lambda+ Architecture, supporting both exploratory and real-time analyzes on data. We propose to study the conservation of properties in composition of components in an architecture using the category theory.
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