Enterprises must deliver data management solutions for large, heterogeneous datasets often composed of disparate data with queries constructed from a variety of programming models. A “one size fits all” mentality just won’t work in these cases. Parallel database management systems (DBMSs) help with performance and federated DBMSs support heterogeneity, but no single engine can support these complex datasets for any but the simplest problems.
In response, new multi-DBMS systems such as Polystore systems have been proposed. These systems combine individual DBMSs, each suited to the needs of a portion of the dataset, into a single system. They are designed to support heterogeneous datasets but do so in a way that exposes the complete functionality and programming models of underlying DBMSs.
At IEEE Big Data’16, BigData’17 we organized workshops on Polystore systems. These successful workshops brought together experts from around the world working on novel advances in the field. Poly’18 will focus on growing a larger and more diverse research agenda around data system solutions for heterogeneous data.
Demonstrations of new tools and techniques for heterogeneous data
Please submit your papers at: https://cmt3.research.microsoft.com/Poly2018/
All submissions will be reviewed. All accepted papers will be made available as proceedings published by Springer.
For a regular paper, the page limit for submission is 10 pages in LNCS format (excluding references). The camera ready version (if accepted) will not have a strict page limit.