Lambda architecture has gained popularity recently as an organizing framework for synthesizing data processing and analysis. However, it has limitations.
In this white paper we demonstrate how – with the addition of a single processing layer – lambda architecture can be generalized and extended for continuous decisioning, providing the same benefits of batch- and stream-processing that standard lambda architecture provides to real-time analytics, as well as providing a continuous feedback mechanism relevant for all applications.
Table of Contents
- Introduction
- Sample Use Case: Real-Time Automated Bank Communications
- Lambda Architecture for Continuous Decisioning
- Implementing the Decisioning Layer with Kamanja
- The Kamanja Community
- References
Co-authors
Co-Authors: Nick Weir and Rich Johnson, LigaData
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