ABSTRACT
Multiple applications from various domains, scientific or enterprise applications, generate huge amounts of data that have to be processed at real-time speed or acquired, cleaned, stored, and ready to be used. Examples of such big data sources could be airplane sensor monitoring to predict future engine crashes and avoid disaster (big data analytics) or a big data platform for modern healthcare. In the context of big data processing challenges, the in-memory computing paradigm has emerged and it is currently used by several big data platforms for data storage/query (in-memory data grids or databases) and for data processing (in-memory computing grids).
