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Cypher Query Language
Cypher is Neo4j’s graph query language that allows users to store and retrieve data from the graph database. Neo4j wanted to make querying graph data easy to learn, understand, and use for everyone, but also incorporate the power and functionality of other standard data access languages. This is what Cypher aims to accomplish.
Cypher’s syntax provides a visual and logical way to match patterns of nodes and relationships in the graph. It is a declarative, SQL-inspired language for describing visual patterns in graphs using ASCII-Art syntax. It allows us to state what we want to select, insert, update, or delete from our graph data without a description of exactly how to do it. Through Cypher, users can construct expressive and efficient queries to handle needed create, read, update, and delete functionality.
Cypher is not only the best way to interact with data and Neo4j – it is also open source! The openCypher project provides an open language specification, technical compatibility kit, and reference implementation of the parser, planner, and runtime for Cypher. It is backed by several companies in the database industry and allows implementors of databases and clients to freely benefit from, use, and contribute to the development of the openCypher language.
These developer guides and tutorials show you how to construct queries in Cypher to store and retrieve data from Neo4j. There are a variety of ways to learn Cypher. Feel free to check out our other Cypher learning tools, as well!
The first two guides will explain the basic concepts of Cypher query syntax, including how to create and query data. Cypher is based on ASCII art, so the syntax is easily understood and makes queries more self-explanatory. It focuses on the clarity of expressing what to retrieve from a graph, not on how to retrieve it.
We will discuss the keywords for each CRUD operation and how to specify nodes, relationships, and properties in the query language. Learning how to specify patterns and filter data results will allow you to traverse the graph or add and remove data.
Most types of queries are not simple data entry or retrieval. Often, you will need to write queries that retrieve sets of data that fall within certain criteria. This is where the capability to filter query results becomes very valuable.
Being able to trim out results that are unwanted and only retrieve certain data is important for application functionality and user experience, but also increases update and read performance because it is only returning results that the user cares about.
In this guide, we will walk through many of the ways you can limit your query results to what you need and control how they are returned to output. Much of the syntax and functionality for these clauses is similar to SQL and will probably be familiar to most developers with data querying experience.
Just as in most programming languages, some utility capabilities are needed to perform basic functions on data being retrieved from a database. Functionality such as counting results, grouping data by values, and finding minimum/maximum values are often bundled into the language itself to provide those capabilities in a standard, out-of-the-box way to all developers.
Cypher also includes these functions to perform mathematical, aggregation, and other utility operations needed within queries. This guide will show you what is possible within Cypher and show you how to structure the syntax.
With the release of Neo4j 3.4, Cypher added support for native date types in the database. Working with dates, datetimes, timezones, and durations is a necessary part of data and databases.
From converting certain values to dates, creating instants, or calculating durations, this guide will cover the basics in using Cypher for Neo4j native date types.
Many query languages include the capability to run subqueries inside outer queries, and Cypher offers this, as well. There are a couple of different approaches to syntax, depending on the type of subquery needed.
We can use existential subqueries to filter more complex scenarios like patterns and even entire nested queries for more accurate and focused results. We can also use result-returning subqueries to sort and order filtered results. While organizing filtered results was previously possible in Cypher, providing subquery support allows us to simplify the syntax and avoid using APOC procedures or additional Cypher clauses to pass and sort values along the way.
Some syntax in Cypher requires a specific style or casing, while other Cypher syntax is not particular on styling. In either case, we have compiled some of the recommended and required styling for writing Cypher queries. This guide will walk through various components of typical syntax to help you write logical and readable Cypher queries.
Cypher was based upon the power and capabilities of SQL – the standard for querying relational databases. However, Cypher was designed and optimized specifically for graph data and traversals. While neither language is better or worse, they each have their strengths and purposes.
SQL developers will see certain keywords and constructs that are the same or very similar to their existing knowledge in the predecessor language. This guide was written with SQL developers in mind to bridge the gap and bring existing knowledge across to learning Cypher. Through examples of both languages, you will see the logic structures and syntax of each and how each was designed for their purpose.
Cypher provides powerful capabilities out-of-the-box. However, developers may need or want additional functionality for business cases or special scenarios. Extending Cypher in Neo4j is simple with user-defined procedures and functions.
User-defined procedures and functions can be written for a variety of cases and simple or complex operations. This guide will show you how to create custom add-ons and how to compile them so that the database recognizes it as part of Cypher.
Before we get too carried away with creating all of our functionality custom, though, we will also talk about how certain libraries and functionality have already been developed to work seamlessly with Neo4j. Learn where you can look to find out if code already exists for your capability or if you need to write your own custom functionality!
With Cypher structure and syntax learned so far, you can dive into building your own recommendation engine to use graph data and Cypher to recommend movies, colleagues, cuisines, and more.
This guide will walk through using queries and filtering that takes advantage of the relationships in a graph in order to lend insight into habits and hidden connections and provide valuable recommendations.
Find out where else you can learn Cypher or increase your depth of knowledge from experts and solutions. There are a variety of training opportunities, blogs, videos, and more for taking the next steps in your Cypher (and Neo4j) journey!