  We present TigerGraph, a graph database system built from the ground up to
support massively parallel computation of queries and analytics.
  TigerGraph's high-level query language, GSQL, is designed for compatibility
with SQL, while simultaneously allowing NoSQL programmers to continue thinking
in Bulk-Synchronous Processing (BSP) terms and reap the benefits of high-level
specification.
  GSQL is sufficiently high-level to allow declarative SQL-style programming,
yet sufficiently expressive to concisely specify the sophisticated iterative
algorithms required by modern graph analytics and traditionally coded in
general-purpose programming languages like C++ and Java.
  We report very strong scale-up and scale-out performance over a benchmark we
published on GitHub for full reproducibility.
