2014 · 21 citations · 4 references
EngineeringMassive VolumeIot CommunicationBig Data AnalyticsDatabasesIot InteroperabilityDatabase BenchmarkingStorage SystemsDatabase SystemData ScienceDatabase SupportManagementSystems EngineeringData IntegrationOperational DataInternet Of ThingsData ManagementData ModelingPi ServerDatabase TechnologyIot Data ManagementTemporal DatabaseRelational QueriesIot Data AnalyticsData ArchitectureIndustrial InformaticsBig Data
In the era of the Internet of Things (IoT), increasing numbers of applications face the challenge of using current data management systems to manage the massive volume of operational data gener-ated by sensors and devices. Databases based on time series data model, like PI Server, are developed to handle such data with operational technology (OT) characteristics (high volume, long lifecycle, and simple format). However, while achieving excellent write performance, these database systems provide limited query capabilities. In this paper, we present the next-generation Opera-tional Data Historian (ODH) system that is based on the IBM© Informix© system architecture. The system combines the write advantages of the existing time series databases and the ability to run complex queries in SQL. We demonstrate the high efficiency of our system for both writing and querying data with a variety of case studies in the industries of Energy and Utilities and con-nected vehicles. In addition, we present the first benchmark, IoT-X, to evaluate technologies on operational data management for IoT.
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