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Ultra-Scalable and Ultra-Efficient Integrated and Visual Big Data Analytics

LeanBigData aims at addressing three open challenges in big data analytics:

  • The cost, in terms of resources, of scaling big data analytics for streaming and static data sources;
  • The lack of integration of existing big data management technologies and their high response time;
  • The insufficient end-user support leading to extremely lengthy big data analysis cycles.

LeanBigData will address these challenges by: Architecting and developing three resource-efficient Big Data management systems typically involved in Big Data processing: a novel transactional NoSQL key-value data store, a distributed complex event processing (CEP) system, and a distributed SQL query engine. We will achieve at least one order of magnitude in efficiency by removing overheads at all levels of the big-data analytics stack and we will take into account technology trends in multicore technologies and non-volatile memories. Providing an integrated big data platform with these three main technologies used for big data, NoSQL, SQL, and Streaming/CEP that will improve response time for unified analytics over multiple sources and large amounts of data avoiding the inefficiencies and delays introduced by existing extract-transfer-load approaches.

Project Partners

Institute Of Communication And Computer Systems