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Graphs are widespread data structures used to model a wide variety ofproblems. The sheer amount of data to be processed has prompted the creation ofa myriad of systems that help us cope with massive scale graphs. The pressureto deliver fast responses to queries on the graph is higher than ever before,as it is demanded by many applications (e.g. online recommendations, auctions,terrorism protection, etc.). In addition, graphs change continuously (so do thereal world entities that typically represent). Systems must be ready for both:near real-time and dynamic massive graphs. We survey systems taking theirscalability, real-time potential and capability to support dynamic changes tothe graph as driving guidelines. The main techniques and limitations aredistilled and categorised. The algorithms run on top of graph systems are notready for prime time dynamism either. Therefore,a short overview on dynamicgraph algorithms has also been included.

Systems for Near Real-Time Analysis of Large-Scale Dynamic Graphs