1. 附:相关图描述语言
- 本体语言学习笔记, https://blog.csdn.net/shendeguang/article/details/8241164
- OWL中基于具体化的多元关系表示研究, https://doc.mbalib.com/view/1754a797116a45923bfaa7a1db86ce0e.html
- 知识图谱---描述语言, https://blog.csdn.net/github_37002236/article/details/81908394
- 知识图谱基础之RDF,RDFS与OWL, https://blog.csdn.net/u011801161/article/details/78833958
- 语义Web简单综述(XML、RDF、OWL、知识库、知识图谱), https://blog.csdn.net/hohaizx/article/details/80043623
- HugeGraph,Neo4j,Titan三种图数据库性能对比, https://www.jianshu.com/p/c124f748877d
官网给了一个性能测试的报告:https://hugegraph.github.io/hugegraph-doc/performance/hugegraph-benchmark-0.5.6.html
总结起来就是:
- 批量插入性能:HugeGraph(RocksDB) > Neo4j > Titan(thrift+Cassandra)
- 遍历性能:Neo4j > HugeGraph(RocksDB) > Titan(thrift+Cassandra)
- 图常用分析方法性能:FS场景,HugeGraph性能优于Neo4j和Titan,K-neighbor和K-out场景,HugeGraph能够实现在5度范围内秒级返回结果
- 社区聚类算法性能 Neo4j > HugeGraph > Titan