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.

 

 

 

 

 

Co-Authors: Nick Weir and Rich Johnson, Ligadata


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

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