%0 Conference Paper
%B Proceedings of the 6th International Conference on Cloud Computing and Services Science
%D 2016
%T Towards Quantifiable Eventual Consistency
%A Francisco Maia
%A Miguel Matos
%A Fábio Coelho
%P 368-370
%R 10.5220/0005929103680370
%X <p>In the pursuit of highly available systems, storage systems began offering eventually consistent data models. These models are suitable for a number of applications but not applicable for all. In this paper we discuss a system that can offer a eventually consistent data model but can also, when needed, offer a strong consistent one.</p>
%Z <p>n/a</p>
%@ 978-989-758-182-3
%> https://haslab.uminho.pt/sites/default/files/fmaia/files/datadiversityconvergence_2016_5.pdf