Integrating Heterogeneous Stream and Historical Data Sources using SQL

Abstract

Applications capable of integrating data from historical and streaming sources can make the most contextualized and enriched decision-making. However, the complexity of data integration over heterogeneous data sources can be a hard task for querying in this context. Approaches that facilitate data integration, abstracting details and formats of the primary sources can meet these needs. This work presents a framework that allows the integration of streaming 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 relational datasets and real data produced by sensors. The results point to the feasibility of the approach.

Towards a Microservice-Based Middleware for a Multi-hazard Early Warning System

“…The specifications and requirements of existing EWS are extremely different depending on the application area, leading to ad-hoc implementations of monolithic software applications and cumbersome legacy systems. The integration of several related EWS has inherent challenges, which are mostly data incompatibility and system interoperability due to heterogeneity, reliability, availability, transparency and abstractions to applications [2], [20][21], [35][36], inhibiting the possibility of harnessing an integrated MHEWS.…”