Abstract
Building cloud data-intensive applications often requires using multiple data stores (NoSQL, HDFS, RDBMS, etc.), each optimized for one kind of data and tasks. However, the wide diversification of data store interfaces makes it difficult to access and integrate data from multiple data stores. This important problem has motivated the design of a new generation of systems, called multistore systems, which provide integrated or transparent access to a number of cloud data stores through one or more query languages. In this paper, we give an overview of query processing in multistore systems. We start by introducing the recent cloud data management solutions and query processing in multidatabase systems. Then, we describe and analyze some representative multistore systems, based on their architecture, data model, query languages and query processing techniques. To ease comparison, we divide multistore systems based on the level of coupling with the underlying data stores, i.e. loosely-coupled, tightly-coupled and hybrid. Our analysis reveals some important trends, which we discuss. We also identify some major research issues.
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