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Modern applications commonly need to manage dataset types composed ofheterogeneous data and schemas, making it difficult to access them in anintegrated way. A single data store to manage heterogeneous data using a commondata model is not effective in such a scenario, which results in the domaindata being fragmented in the data stores that best fit their storage and accessrequirements (e.g., NoSQL, relational DBMS, or HDFS). Besides, organizationworkflows independently consume these fragments, and usually, there is noexplicit link among the fragments that would be useful to support an integratedview. The research challenge tackled by this work is to provide the means toquery heterogeneous data residing on distinct data repositories that are notexplicitly connected. We propose a federated database architecture by providinga single abstract global conceptual schema to users, allowing them to writetheir queries, encapsulating data heterogeneity, location, and linkage byemploying: (i) meta-models to represent the global conceptual schema, theremote data local conceptual schemas, and mappings among them; (ii) provenanceto create explicit links among the consumed and generated data residing inseparate datasets. We evaluated the architecture through its implementation asa polystore service, following a microservice architecture approach, in ascenario that simulates a real case in Oil \& Gas industry. Also, we comparedthe proposed architecture to a relational multidatabase system based on foreigndata wrappers, measuring the user's cognitive load to write a query (or querycomplexity) and the query processing time. The results demonstrated that theproposed architecture allows query writing two times less complex than the onewritten for the relational multidatabase system, adding an excess of no morethan 30% in query processing time.

A Polystore Architecture Using Knowledge Graphs to Support Queries on Heterogeneous Data Stores