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EnterpriseGraphs enable you to manage graphs at scale with automated sharding key selection

ArangoDB Enterprise Edition ArangoGraph

This chapter describes the enterprise-graph module, a specialized version of SmartGraphs. It will give a vast performance benefit for all graphs sharded in an ArangoDB Cluster, reducing network hops substantially.

In terms of querying there is no difference between SmartGraphs and EnterpriseGraphs. For graph querying please refer to AQL Graph Operations and General Graph Functions sections.

Creating and modifying the underlying collections of an EnterpriseGraph are also similar to SmartGraphs. For a detailed API reference, please refer to Enterprise Graphs Management.

Coming from the Community Edition? See how to migrate from a general-graph to an enterprise-graph.

How EnterpriseGraphs work

The creation and usage of EnterpriseGraphs are similar to SmartGraphs. However, the latter requires the selection of an appropriate sharding key. This is known as the smartGraphAttribute, a value that is stored in every vertex, which ensures data co-location of all vertices sharing this attribute and their immediate edges.

EnterpriseGraphs come with a concept of “random sharding”, meaning that the sharding key is randomly selected while ensuring that all vertices with the same sharding key and their adjacent edges are co-located on the same servers, whenever possible. This approach provides significant advantages as it minimizes the impact of having suboptimal sharding keys defined when creating the graph.

This means that, when using EnterpriseGraphs, the smartGraphAttribute is not required. As a consequence, you cannot define _key values on edges.

EnterpriseGraphs using SatelliteCollections

EnterpriseGraphs are capable of using SatelliteCollections within their graph definition. Therefore, edge definitions defined between EnterpriseCollections and SatelliteCollections can be created. As SatelliteCollections (and the edge collections between EnterpriseGraph collections and SatelliteCollections) are globally replicated to each participating DB-Server, (weighted) graph traversal and (k-)shortest path(s) query can partially be executed locally on each DB-Server. This means a larger part of the query can be executed fully local whenever data from the SatelliteCollections is required.