  This paper introduces GTX a standalone main-memory write-optimized graph
system that specializes in structural and graph property updates while
maintaining concurrent reads and graph analytics with snapshot isolation-level
transactional concurrency. Recent graph libraries target efficient concurrent
read and write support while guaranteeing transactional consistency. However,
their performance suffers for updates with strong temporal locality over the
same vertexes and edges due to vertex-centric lock contentions. GTX introduces
a new delta-chain-centric concurrency-control protocol that eliminates
traditional mutually exclusive latches. GTX resolves the conflicts caused by
vertex-level locking, and adapts to real-life workloads while maintaining
sequential access to the graph's adjacency lists storage. This combination of
features has been demonstrated to provide good performance in graph analytical
queries. GTX's transactions support fast group commit, novel write-write
conflict prevention, and lazy garbage collection. Based on extensive
experimental and comparative studies, in addition to maintaining competitive
concurrent read and analytical performance, GTX demonstrates high throughput
over state-of-the-art techniques when handling concurrent transaction+analytics
workloads. For write-heavy transactional workloads, GTX performs up to 11x
better than the best-performing state-of-the-art systems in transaction
throughput. At the same time, GTX does not sacrifice the performance of
read-heavy analytical workloads, and has competitive performance similar to
state-of-the-art systems.
