Polyglot Database Architectures = Polyglot Challenges
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We categorize polyglot database architectures into three types (polyglot persistence, lambda architecture and multi-model databases) and discuss their advantages and disadvantages. 1 Polyglot Database Architectures When designing the data management layer for an application, several database requirements may be contradictory. For example, regarding access patterns some data might be accessed by write-heavy workloads while others are accessed by read-heavy workloads. Regarding the data model, some data might be of a different structure than other data; for example, in an application processing both social network data and order or billing data, the former might usually be graphstructured while the latter might be semi-structured data. Regarding the access method, a web application might want to access data via a REST interface while another application might prefer data access with query language. It is hence worthwhile to consider a database and storage architecture that includes all these requirements. We describe three option for polyglot database architectures in the following three sections. 1.1 Polyglot Persistence Instead of choosing just one single database management system to store the entire data, so-called polyglot persistence could be a viable option to satisfy all requirements towards a modern data management infrastructure. Polyglot persistence (a term coined in [4]) denotes that one can choose as many databases as needed so that all requirements are satisfied. Polyglot persistence can in particular be an optimal solution when backward-compatibility with a legacy application must be ensured. The new database system can run alongside the legacy Copyright c © 2015 by the paper’s authors. Copying permitted only for private and academic purposes. In: R. Bergmann, S. Gorg, G. Muller (Eds.): Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. Trier, Germany, 7.-9. October 2015, published at http://ceur-ws.org
[1] Nathan Marz,et al. Big Data: Principles and best practices of scalable realtime data systems , 2015 .
[2] Martin Fowler,et al. NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence , 2012 .
[3] Andrey Gubarev,et al. Dremel : Interactive Analysis of Web-Scale Datasets , 2011 .