Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.14778/3007263.3007265 | PVLDB |
Field | DocType | Volume |
Data mining,Programming language,Computer science,Theoretical computer science,SPQR tree,Domain-specific language,Graph database,Power graph analysis,Wait-for graph,Graph rewriting,Data model,Graph (abstract data type),Database | Journal | 9 |
Issue | ISSN | Citations |
13 | 2150-8097 | 4 |
PageRank | References | Authors |
0.42 | 17 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Sevenich | 1 | 14 | 1.25 |
| Sungpack Hong | 2 | 864 | 33.20 |
| Oskar van Rest | 3 | 52 | 3.31 |
| Zhe Wu | 4 | 19 | 1.29 |
| Jay Banerjee | 5 | 984 | 422.56 |
| Hassan Chafi | 6 | 1118 | 61.11 |