What is the query language Cypher?
Cypher is a declarative Query language, the for working with graph databases was developed. Graph databases are specialised Databasesthat organise data in the form of nodes and edges in a graph model. Nodes represent entities, while edges represent relationships between entities. One of the leading graph databases is Neo4jfor which Cypher was specially developed.
With Cypher it is possible to search, analyse and manipulate complex patterns and relationships in a graph. Thus, complex queries and operations on graph-based data structures can be performed efficiently and easily.
The syntax of Cypher is Simple and intuitive, which makes it easier to work with graph-based data structures. A basic query consists of a combination of patterns applied to the graph to search for specific Entities or relationships. A pattern in Cypher is usually written in brackets and can consist of nodes, edges or both.
A simple example of a Cypher query looks like this:
WHERE n.name = 'Alice
This query searches for persons (nodes with the label "Person") followed by a specific person named Alice. The pattern "(n:Person)-[:FOLLOWS]->(m:Person)" indicates that there must be a relationship with the name "FOLLOWS" from a node with the label "Person" to another node with the label "Person". The "WHERE" clause sets a condition for searching for persons named "Alice" and the "RETURN" clause returns the name of the persons found.
Areas of application for Cypher
Cypher is used in various application areas to perform complex queries and operations on graph-based data structures. Here are three common application areas of Cypher:
- Social network analysisCypher is ideal for analysing social networks, as they are often modelled as graphs. This allows relationships between people, organisations or other entities in a social network to be explored efficiently. For example, queries can be used to identify common friends, influencers or key players in a social network.
- Recommendation systemsCypher can also be used to create recommendation systems based on graph-based data structures. This will identify complex patterns and relationships between entities to generate personalised recommendations for users. For example, queries in Cypher can be used to find common interests, connections or similar profiles of users to create recommendations for products, services or content.
- Fighting fraud: Cypher is also used to combat fraud, as it allows complex relationships and patterns in large amounts of data to be analysed. Queries can be created to identify suspicious connections, unusual behaviour patterns or potential fraud networks. This can be used in various industries such as financial services, e-commerce or insurance to detect and prevent fraud at an early stage.