The Great Graph Debate: Revolutionary concept in databases or niche curiosity?
Andy Pavlo'Graph DBMSs garner more attention and mindshare than is warranted'
Recently there has been a lot of academic and industry interest in graph databases and their related ilks, such as the and triplestores. This is because many developers use knowledge graphs for modeling relationships in their applications. For example, social media applications inherently contain graph-oriented relationships . Given this, we have seen the advent of graph-oriented DBMSs in the last two decades. These systems either target operational workloads or analytical workloads .
But we contend that this interest is misguided: graph DBMSs garner more attention and mindshare than is warranted. These systems ignore many of the hard-learned lessons on data management from the last 50 years. As we now discuss, the graph DBMSs are fundamentally flawed and, for most applications, inferior to relational DBMSs.
We first note that the idea of natively storing databases in a graph-oriented manner is not new. CODASYL was a network data model proposed in the 1970s for querying and updating a database. Modern graph DBMSs inherit almost the same problems as their CODASYL predecessors. For example, they provide a low-level access language that lacks data independence.
This limitation alone should be a dealbreaker for any sensible practitioner. But developers continue to think that graph DBMSs are better for graph-data problems than relational DBMSs. This likely is because, in addition to graph-native storage, these DBMSs also support graph-oriented query languages .A relational DBMS traverses edges in a graph through joins.
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