Using Domain-Specific Languages For Analytic Graph Databases


Recently graph has been drawing lots of attention both as a natural data model that captures fine-grained relationships between data entities and as a tool for powerful data analysis that considers such relationships. In this paper, we present a new graph database system that integrates a robust graph storage with an efficient graph analytics engine. Primarily, our system adopts two domain-specific languages (DSLs), one for describing graph analysis algorithms and the other for graph pattern matching queries. Compared to the API-based approaches in conventional graph processing systems, the DSL-based approach provides users with more flexible and intuitive ways of expressing algorithms and queries. Moreover, the DSL-based approach has significant performance benefits as well, (1) by skipping (remote) API invocation overhead and (2) by applying high-level optimization from the compiler.

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@article{Sevenich2016UsingDL, title={Using Domain-Specific Languages For Analytic Graph Databases}, author={Martin Sevenich and Sungpack Hong and Oskar van Rest and Zhe Bao Wu and Jay Banerjee and Hassan Chafi}, journal={PVLDB}, year={2016}, volume={9}, pages={1257-1268} }