Polystore Data Management Systems for Managing Scientific Data-sets in Big Data Archives

  • Rashmi Girirajkumar Patidar
  • Shashank Shrestha
  • Subhash BhallaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11297)


Large scale scientific data sets are often analyzed for the purpose of supporting workflow and querying. User need to query over different data sources. These systems manage intermediate results. Most prototypes are complex and have an ad hoc design. These require extensive modifications in case of growth of data and change of scale, in terms of data or number of users. New data sources may arise to further complicate the ad hoc design. The polystore data management approach provides ‘data independence’ for changes in data profile, including addition of cloud data resources. The users are often provided a quasi-relational query language. In many cases, the polystore systems support distinct tasks that are user defined workflow activity, in addition to providing a common view of data resources.


Big data analytics Cloud-based databases Heterogeneous data Distributed data Polystore data management Query language support Scalability 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Rashmi Girirajkumar Patidar
    • 1
  • Shashank Shrestha
    • 1
  • Subhash Bhalla
    • 1
    Email author
  1. 1.Department of Information SystemsUniversity of AizuFukushimaJapan

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