Real time processing technologies in big data: Comparative study

Recently, increasingly huge amounts of data are generated from a variety of sources. It has become crucial to track all kinds of information over time hence real-time processing is eagerly needed. It has become a challenge to achieve the real-time capability using the traditional technologies which are not suitable to cope with huge amounts of generated data. Several distributed data processing systems have emerged that deviate from the batch oriented approach and tackle data items as they arrive, thus acknowledging the growing importance of timeliness and velocity in Big Data analytics. Yet, many researches focus on data processing. In our paper, we give an overview of the state of art of the existing solutions for real time data processing and conduct a qualitative comparison of the most popular frameworks. We describe their respective underlying rationales, the guarantees they provide and discuss the trade-offs that come with selecting one of them for a particular task.