Abstract
The complexity imposed by data heterogeneity makes it difficult to integrate 'streaming x streaming' and 'streaming x historical' data types. For practical analysis, the enrichment and contextualization process based on historical and streaming data would benefit from approaches that facilitate data integration, abstracting details and formats of the primary sources. This work presents a framework that allows the integration of streaming data and historical data in real-time, abstracting syntactic aspects of queries through the use of SQL as a standard language for querying heterogeneous sources. The framework was evaluated through an experiment using a relational database and real data produced by sensors. The results point to the feasibility of the approach.
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