Abstract
A conceptual data persistence architecture and methodology to evaluate its performance is created. Results of the empirical research indicate that the architecture created is convenient for high intensity processing of large ECM data volumes. The synthesis of SQL and NoSQL technology allows to handle high volume transactions on current data and full-text search on large sets of history data. The history data is moved from SQL to NoSQL data store thus allowing to use a cluster of commodity hardware to store major volume of ECM data. Scaling out (increasing a number of cluster nodes) is less expensive than scaling up (buying a more powerful server hardware) that is normally needed to upgrade SQL database.
Keywords
MSC
68M14, 68U35
Cite this article
@article{cai-4445,
author = {Juris Rats},
title = {Developing and Evaluating ECM Data Persistence Architecture},
journal = {Computing and Informatics},
volume = {38},
number = {2},
pages = {454--472},
year = {2019},
issn = {1335-9150},
doi = {10.31577/cai_2019_2_454}
}
TY - JOUR AU - Juris Rats TI - Developing and Evaluating ECM Data Persistence Architecture JO - Computing and Informatics VL - 38 IS - 2 SP - 454 EP - 472 PY - 2019 SN - 1335-9150 DO - 10.31577/cai_2019_2_454 UR - https://doi.org/10.31577/cai_2019_2_454 KW - Polyglot persistence KW - NoSQL KW - ECM KW - Elasticsearch KW - hot-warm architecture ER -
Rats, J. (2019). Developing and Evaluating ECM Data Persistence Architecture. Computing and Informatics, 38(2), 454–472. https://doi.org/10.31577/cai_2019_2_454