With the development of science and technology, the data size and complexity of scientific data are increased rapidly, which made efficient data storage and parallel analysis of scientific data become a big challenge. The previous techniques that combine the traditional relational database with analysis software tends cannot efficiently meet the performance requirement of large scale scientific data based analysis. In this paper, we present FASTDB, a distributed array database system that optimized for massive scientific data management and provide a share-nothing, parallel array processing analysis. In order to demonstrate the intrinsic performance characteristics of FASTDB, we applied it into the interactive analysis of data from astronomical surveys, and designed a series of experiments with scientific analysis tasks. According to the experimental results, we found FASTDB can be significantly fast than traditional database based SkyServer in many typical analytical scenarios.
CITATION STYLE
Li, H., Qiu, N., Chen, M., Li, H., Dai, Z., Zhu, M., & Huang, M. (2015). FASTDB: An array database system for efficient storing and analyzing massive scientific data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9532, pp. 606–616). Springer Verlag. https://doi.org/10.1007/978-3-319-27161-3_55
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