Graph Databases
Graph data is very common in modern applications. The property of this kind of data is the high levels of connectivity between the entities. Although social networks are the most common example for demonstrating graph data and the importance of graph databases, graphs are not limited to social networks; many other applications can be modeled much more clearly and intuitively with graphs. Once we model our data as a graph, we usually want to explore certain parts of the graph to find relations or interesting patterns. That includes simple use cases such as finding a person's friends or friend-of-friends in a social network, or complex patterns revealing frauds in a financial graph. All these applications require fast traversal of graph nodes. Although we can store a graph in a tabular relational database or a NoSQL database such as key-value/document stores, they typically don't provide fast traversal which is critical for graph applications. In this p