1 research outputs found
Systems for Near Real-Time Analysis of Large-Scale Dynamic Graphs
Graphs are widespread data structures used to model a wide variety of
problems. The sheer amount of data to be processed has prompted the creation of
a myriad of systems that help us cope with massive scale graphs. The pressure
to 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 the
real world entities that typically represent). Systems must be ready for both:
near real-time and dynamic massive graphs. We survey systems taking their
scalability, real-time potential and capability to support dynamic changes to
the graph as driving guidelines. The main techniques and limitations are
distilled and categorised. The algorithms run on top of graph systems are not
ready for prime time dynamism either. Therefore,a short overview on dynamic
graph algorithms has also been included