NoSQL Databases:
NoSQL databases (aka "not only SQL") are non-tabular databases and store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. The main types are document, key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of data and high user loads.
Most NoSQL systems are aggregate-oriented, grouping the data based on a particular criterion and the database type (such as document store, key-value pair, etc). This model provides only simple, limited operations and only forms one dedicated view of your data. Focusing on one aggregate at a time allows users to easily spread many chunks of data across a network of machines along the aggregate dimension (for instance, the Document in document databases), but that means that other projections and perspectives have to be computed by crunching or duplicating your data.
Graph Databases:
A graph in a graph database can be traversed along specific edge types or across the entire graph. In graph databases, traversing the joins or relationships is very fast because the relationships between nodes are not calculated at query times but are persisted in the database. Graph databases have advantages for use cases such as social networking, recommendation engines, and fraud detection, when you need to create relationships between data and quickly query these relationships.
Graph databases are purpose-built to store and navigate relationships. Relationships are first-class citizens in graph databases, and most of the value of graph databases is derived from these relationships. Graph databases use nodes to store data entities, and edges to store relationships between entities. An edge always has a start node, end node, type, and direction, and an edge can describe parent-child relationships, actions, ownership, and the like. There is no limit to the number and kind of relationships a node can have.
Graph databases, on the other hand, handle fine-grained networks of information, providing any perspective on your data that fits your use case. The well-known and trusted transactional guarantees from relational systems also protect updates of the graph data in Neo4j, conforming to ACID standards.
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