Finding Your Way Through the Jungle of Big Data Architectures
Databases
2022-01-24 v1
Abstract
This paper presents a systematic review of common analytical data architectures based on DAMA-DMBOK and ArchiMate. The paper is work in progress and provides a first view on Gartner's Logical Data Warehouse paradigm, Data Fabric and Dehghani's Data Mesh proposal as well as their interdependencies. It furthermore sketches the way forward how this work can be extended by covering more architecture paradigms (incl. classic Data Warehouse, Data Vault, Data Lake, Lambda and Kappa architectures) and introducing a template with among others "context", "problem" and "solution" descriptions, leading ultimately to a pattern system providing guidance for choosing the right architecture paradigm for the right situation.
Keywords
Cite
@article{arxiv.2201.04233,
title = {Finding Your Way Through the Jungle of Big Data Architectures},
author = {Torsten Priebe and Sebastian Neumaier and Stefan Markus},
journal= {arXiv preprint arXiv:2201.04233},
year = {2022}
}
Comments
3 pages, 4 figures