English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

During the development of NoSQL-backed software, the data model evolvesnaturally alongside the application code. Especially in agile development, newapplication releases are deployed frequently causing schema changes.Eventually, decisions have to be made regarding the migration of versionedlegacy data which is persisted in the cloud-hosted production database. Wesolve this schema evolution problem and present the results of near-exhaustivecalculations by means of which software project stakeholders can manage theoperative costs for data model evolution and adapt their software releasestrategy accordingly in order to comply with service-level agreements regardingthe competing metrics of migration costs and latency. We clarify conclusivelyhow data model evolution in NoSQL databases impacts the metrics while takingall relevant characteristics of migration scenarios into account. Ascalculating all possible combinatorics in the search space of migrationscenarios would by far exceed computational means, we used a probabilisticMonte Carlo method of repeated sampling, serving as a well-established means tobring the complexity of data model evolution under control. Our experimentsshow the qualitative and quantitative impact on the performance of migrationstrategies with respect to intensity and distribution of data entity accesses,the kinds of schema changes, and the characteristics of the underlying datamodel.

MigCast in Monte Carlo: The Impact of Data Model Evolution in NoSQL Databases