NEO4J Diagram Database Introduction

The graph database stores the data in the diagram, which is the most common data structure. Graphs can store nodes and relationships, and nodes and relationships can hold properties. The data model for this storage graph is called a property map.

Basic elements in the graph database

Nodes are often used to represent entities, and nodes can be labeled by multiple tags. The simplest attribute graph is a graph of only one node, which can have multiple key-value pair-tag attributes. A relationship organizes nodes by connecting nodes, a connection with two nodes, a start node, and an end node. This indicates that the relationship has a direction. The relationship can be used to organize nodes into linked lists, trees, graphs and other data structures. Tags are used to assign node roles and types. A node can have more than one label.

Advanced properties in the figure data

A traversal (traversal) is used to find the path in the diagram. A traversal indicates how to query a diagram, directing how to start a node to a relational node. Traversing a graph means accessing the nodes in the graph according to certain rules, usually only a subset of the sub-graphs can be accessed. The NEO4J database provides a declarative cypher language to query the graph, and neo4j generates a traversal scheme to query the graph. You can also specify the traversal scheme directly, specifying depth first or breadth first.

Indexes in NEO4J can be used to speed up queries, and indexing in neo4j returns immediately, but does not mean that the index is immediately established and the index is available after the final build, known as final availability.

Constraints, which can be established in neo4j, constraints are a set of rules that do not satisfy the rules are not accepted.

NEO4J Diagram Database Introduction