AlertMix: A Big Data platform for multi-source streaming data
This addresses the need for real-time stream processing in applications like trading and fraud detection, but it appears incremental as it builds on existing big data technologies.
The authors tackled the problem of processing multi-source streaming data in real-time by developing AlertMix, an end-to-end big data platform, and demonstrated its performance on live streaming data.
The demand for stream processing is increasing at an unprecedented rate. Big data is no longer limited to processing of big volumes of data. In most real-world scenarios, the need for processing stream data as it comes can only meet the business needs. It is required for trading, fraud detection, system monitoring, product maintenance and of course social media data such as Twitter and YouTube videos. In such cases, a "too late architecture" that focuses on batch processing cannot realize the use cases. In this article, we present an end to end Big data platform called AlertMix for processing multi-source streaming data. Its architecture and how various Big data technologies are utilized are explained in this work. We present the performance of our platform on real live streaming data which is currently handled by the platform.