Main Features Neo4j JanusGraph HugeGraphOpen Source EcologyThe community version is open source, the commercial version is closed sourceOpen source, compatible with the Apache Tinkerpop ecosystem, mainly provided by IBM on cloud services.(Janus has added few features since 2015 forked from Titan)Open source, compatible with the Apache Tinkerpop ecosystem. (HugeGraph has continued to add a large number of features with active state since 2017)Technology ArchitectureStand-alone version architecture, graph storage structure adopts adjacency linked list, suitable for scenarios where small-scale graphs can be accommodated in memory (linked lists are not suitable for query on disk)Share-Storage architecture, graph storage structure adopts adjacency sequence table, mainly adopts HBase as back-end storageShare-Storage architecture, Share-Nothing architecture (RocksDB), graph storage structure adopts adjacent sequence table, single-machine can support billion-level graphs, read and write performance is much higher than Titan/JanusData ScaleCommunity version billion-level, stand-alone versionOver 10 billionsOver 100 billionWrite PerformanceOnline import speed is slow (~10k/s) , Offline import speed is faster (10~100k/s)Slow (1~10k/s), especially for graphs above one billion level.Online import is fast (100~500k/s), and supports fast overwriting featureRead Performance10~40 k/s，on 100 million scale graph~10k/s，with performance jitter20~100k, the performance of HugeGraph 0.12 is faster than Neo4j 2x+ on 100 million scales; HugeGraph is faster than Neo4j 5x on the 1 billion scale graphSuper VertexAdjacent edges query of super vertex is slow, and the cross-linked list storage structure is difficult to speed up the query partial of adjacent edgesCan be relieved by Vertex-Centric indexCan be relieved by Vertex-Centric index, and supports access all data by pagingBuilt-in Common Graph AlgorithmsProvides an installation algorithm package, providing graph algorithms like path search, similarity, centrality, community detection, link prediction, etc.Not SupportedBuilt-in provides basic graph algorithms, like path search, collaborative recommendation, centrality, community discovery, etc.Support large-scale Graph ComputingNot SupportedSupport the expansion of Spark GraphX, Giraph, etc.Built-in HugeGraph-Computer, providing large-scale parallel graph computing, in addition to supporting the expansion of Spark GraphXHASupported by Commercial VersionNot SupportedSupported
Original: https://blog.csdn.net/javeme/article/details/122312685
Author: Jermy Li
Title: Comparison of Graph Database: Neo4j, JanusGrraph and HugeGraph
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