What is an example of a graph database often used in Big Data analytics?

Neo4j is recognized as a prominent example of a graph database frequently employed in Big Data analytics due to its capability to efficiently model and analyze interconnected data sets. Graph databases like Neo4j are designed to store and process data in the form of nodes, edges, and properties, which enables them to represent complex relationships and relationships effectively.

This architecture allows for powerful querying capabilities to explore relationships within the data, making it particularly suitable for applications such as social networks, recommendation systems, and fraud detection, where understanding the connections between data points is crucial.

In contrast, the other choices represent different types of databases. MongoDB is a document-oriented NoSQL database, while MySQL and PostgreSQL are relational databases that utilize structured query language (SQL). These alternatives are excellent for other types of data handling, but they lack the specialized features for efficient relationship querying that Neo4j provides, which are key to graph-based analytics tasks.