Metadata-driven Data Migration from Object-relational Database to NoSQL Document-oriented Database

The object-relational databases (ORDB) are powerful for managing complex data, but they suffer from problems of scalability and managing large-scale data. Therefore, the importance of the migration of ORDB to NoSQL derives from the fact that the large volume of data can be handled in the best way with high scalability and availability. This paper reports our metadata-driven approach for the migration of the ORDB to document-oriented NoSQL database. Our data migration approach involves three major stages: a preprocessing stage, to extract the data and the schema's components, a processing stage, to provide the data transformation, and a post-processing stage, to store the migrated data as BSON documents. The approach maintains the benefits of Oracle ORDB in NoSQL MongoDB by supporting integrity constraint checking. To validate our approach, we developed OR2DOD (Object Relational to Document-Oriented Databases) system, and the experimental results confirm the effectiveness of our proposal

Big data integration: A semantic mediation architecture using Summary

This paper presents our semantic mediation architecture for homogeneously retrieving data from big data. The architecture is split into three layers to find relevant answers of this data. In the proposed ontology-based approach, we use our domain ontology on alimentation risks field as well as a global schema of mediator and we apply the summarization process based on ontology for describes part of the data set. Thus, the auto evolution of ontology is based on this huge amount of data. The research of answer is related to relevant summaries which represent high-level semantics