NoSQL Schema Evolution and Data Migration: State-of-the-Art and Opportunities.

Authors: 
Störl, Uta; Klettke, Meike; Scherzinger, Stefanie
Author: 
Störl, U
Klettke, M
Scherzinger, S
Year: 
2020
Venue: 
ER conf
URL: 
http://openproceedings.org/2020/conf/edbt/paper_T4.pdf
Citations range: 
n/a

Recent position papers demand more schema flexibility, such as the ability to handle variational data [3, 42]. Many agile software developers have long since turned towards NoSQL database systems such as MongoDB 1, Couchbase 2, or ArangoDB 3 which are schema-flexible, or even altogether schema-free. They allow to store datasets in different structural versions to co-exist. Yet even when the database management system does not maintain an explicit schema, there is commonly an implicit schema, as the application code makes assumptions about the structure of the stored data. For instance, in Figure 1, the Java code in lines 1 through 9 implies a schema: An entity for person Jo Bloggs is created, and then persisted in the people collection.