Abstract: This paper discussed the management and analysis over data for decision support, which is defined as one of the three categories of big data. In this big data era, business intelligence creates tremendous large market values, while the enhancement in the computer hardware further stimulate the emergence of new data analysis applications, which require interactive data analysis. Based on the detailed analysis of the typical applications, we find that the inmemory cluster computing system will be the future trends for interactive data analysis. In the environment of inmemory cluster computing systems, the network communication has become the main bottleneck when comparing to memory data access and disk I/Os. Hence, the further research topics within the inmemory cluster computing aspects, including the system topology of the distributed sharednothing inmemory computing systems when considering the characteristics of memory (e.g., volatility, memory wall) as well as communication bottleneck, the data placement and index strategies for isomerism, multilevel cache, the parallel computing framework of multi-granularity over multi-core, multi-processor and multicomputer, the data consistency of the distributed data management, data compression and process mechanism over the column wise data storage.

Key words: in-memory data management, cache sensitive, iterative data processing