We have the answers to your questions! - Don't miss our next open house about the data universe!

Neo4j Unveiled: Exploring the Pinnacle of Graph Databases

 m de lecture

To take advantage of the large volumes of complex data at their disposal, companies are now exploiting graph analytics tools. This technology converts Big Data into valuable information. One of the most popular graph-oriented databases is Neo4j. Developers and data scientists use it to take advantage of numerous tools for creating applications or analyzing data.

What is a graph-oriented database?

A graph-oriented database is a type of database for exploring relationships between data. Rather than storing tables or documents, the graph database stores nodes and relationships.

Each node contains data entities, linked together to enable understanding of their relationships. Data is accumulated without being restricted to a predefined model, enabling it to be analyzed and used flexibly.

Within a graph database, a node can have any number and type of relationships. An edge, on the other hand, always has a start node, an end node, a type and a direction. An edge node can also represent a parent-child relationship, actions and a property.

Most companies use graph-oriented databases to analyze large volumes of data. The aim is to extract information from this data and identify connections between them.

Although traditional relational databases can record relationships, their performance is much lower. A graph-oriented database is able to store relationships natively alongside nodes in a flexible, higher-performance format.

What’s more, these databases are optimized for rapid data mining. They are therefore more efficient at extending a data model or adapting it to changing business needs.

What's the difference with a relational database?

A relational database is made up of rows and columns, and relationships between tables are established using keys. This type of database is used in particular for transactional applications.

A graph-oriented database is made up of nodes and borders indicating the relationships between data. It is mainly used for use cases involving numerous relationships between data, such as fraud detection or recommendation engines.

What is Neo4J ?

Neo4J is one of the most popular graph-oriented databases. It offers many advantages.

Its data model is flexible, simple and robust. It can be tailored to the needs of any application, on demand.

This database delivers results based on real-time data. It also delivers high availability for large enterprises’ real-time applications involving transactional contracts.

It is a schema-independent database, offering a direct representation of connected or semi-structured data. Connected data can be retrieved faster than with any other database.

Its declarative query language, Cypher Query Language (CQL), is both direct and comprehensible. This database is very fast and powerful, and does not require complex joins or indexes to find interconnected data.

What’s more, Neo4J supports ACID properties: Atomicity, Consistency, Isolation and Durability. It also offers great flexibility, since it is possible to increase the number of write or read operations and the volume without impacting query processing speed or data integrity.

Another advantage: a Neo4j application for web browsers is available. Its REST API enables it to work with programming languages such as Java, Spring and Scala.

Its Java Script also enables it to work with frameworks such as Node JS. The Cypher and Native Java APIs enable Java applications to be developed. Data can be exported in JSON and XLS formats to work with other databases such as MongoDB and Cassandra.

How do I learn to use Neo4J?

Mastering Neo4J is a real advantage for software development and data science. To learn how to use this tool, you can choose DataScientest training courses.

The database module of our Data Engineer training covers Neo4j, SQL, MongoDB and ElasticSearch. The other modules cover programming, Data Science, Big Data, automation and deployment.

On completion of the course, you will have all the skills required to become a Data Engineer. You’ll be able to design an automated data processing pipeline to meet a company’s needs, as well as deploy Machine Learning models on production servers.

At the end of the program, a certificate issued by MINES ParisTech / PSL Executive Education as part of our partnership will enable you to validate your skills with employers. 80% of our alumni have found immediate employment.

All our courses are delivered entirely by distance learning, and adopt an innovative Blended Learning approach, combining distance learning on our coached platform and Masterclass.

You can choose between Continuing Education and intensive BootCamp mode.

For financing purposes, our programs are eligible for state financing. Don’t waste another moment, and discover our other Data Engineer training courses!

You now know everything about Neo4J. For more information on databases, take a look at our dossier on MongoDB and our complete dossier on ElasticSearch.


DataScientest News

Sign up for our Newsletter to receive our guides, tutorials, events, and the latest news directly in your inbox.

You are not available?

Leave us your e-mail, so that we can send you your new articles when they are published!
icon newsletter


Get monthly insider insights from experts directly in your mailbox