Online and Offline Analysis of Streaming Data
This provides a general architecture for practitioners and academics to handle both online and offline data analysis in one system, though it is incremental as it builds on existing patterns.
The paper tackles the lack of a unified architecture for online and offline analytics of streaming data by proposing a 7-layered design using microservices and publish-subscribe patterns, resulting in a scalable and maintainable solution.
Online and offline analytics have been traditionally treated separately in software architecture design, and there is no existing general architecture that can support both. Our objective is to go beyond and introduce a scalable and maintainable architecture for performing online as well as offline analysis of streaming data. In this paper, we propose a 7-layered architecture utilising microservices, publish-subscribe pattern, and persistent storage. The architecture ensures high cohesion, low coupling, and asynchronous communication between the layers, thus yielding a scalable and maintainable solution. This design can help practitioners to engage their online and offline use cases in one single architecture, and also is of interest to academics, as it is a building block for a general architecture supporting data analysis.