  The abundance of interconnected data has fueled the design and implementation
of graph generators reproducing real-world linking properties, or gauging the
effectiveness of graph algorithms, techniques and applications manipulating
these data. We consider graph generation across multiple subfields, such as
Semantic Web, graph databases, social networks, and community detection, along
with general graphs. Despite the disparate requirements of modern graph
generators throughout these communities, we analyze them under a common
umbrella, reaching out the functionalities, the practical usage, and their
supported operations. We argue that this classification is serving the need of
providing scientists, researchers and practitioners with the right data
generator at hand for their work. This survey provides a comprehensive overview
of the state-of-the-art graph generators by focusing on those that are
pertinent and suitable for several data-intensive tasks. Finally, we discuss
open challenges and missing requirements of current graph generators along with
their future extensions to new emerging fields.
