  Recently, increasingly large amounts of data are generated from a variety of
sources. Existing data processing technologies are not suitable to cope with
the huge amounts of generated data. Yet, many research works focus on Big Data,
a buzzword referring to the processing of massive volumes of (unstructured)
data. Recently proposed frameworks for Big Data applications help to store,
analyze and process the data. In this paper, we discuss the challenges of Big
Data and we survey existing Big Data frameworks. We also present an
experimental evaluation and a comparative study of the most popular Big Data
frameworks. This survey is concluded with a presentation of best practices
related to the use of the studied frameworks in several application domains
such as machine learning, graph processing and real-world applications.
