NMSTREAM: A SCALABLE EVENT-DRIVEN ETL FRAMEWORK FOR PROCESSING HETEROGENEOUS STREAMING DATA
Keywords: Streaming data, Extract-Transform-Load, Apache Flume, Apache Cassandra
Abstract. ETL (Extraction-Transform-Load) tools, traditionally developed to operate offline on historical data for feeding Data-warehouses need to be enhanced to deal with continuously increased streaming data and be executed at network level during data streams acquisition. In this paper, a scalable and web-based ETL system called NMStream was presented. NMStream is based on event-driven architecture and designed for integrating distributed and heterogeneous streaming data by integrating the Apache Flume and Cassandra DB system, and the ETL processes were conducted through the Flume agent object. NMStream can be used for feeding traditional/real-time data-warehouses or data analytic tools in a stable and effective manner.