What is a Graph Database?

We live in a connected world, and understanding most domains requires processing rich sets of connections to understand what’s really happening. Often, we find that the connections between items are as important as the items themselves.

How else do people do this today? While existing relational databases can store these relationships, they navigate them with expensive JOIN operations or cross-lookups, often tied to a rigid schema. It turns out that "relational" databases handle relationships poorly. In a graph database, there are no JOINs or lookups. Relationships are stored natively alongside the data elements (the nodes) in a much more flexible format. Everything about the system is optimized for traversing through data quickly; millions of connections per second, per core.

Graph databases address big challenges many of us tackle daily. Modern data problems often involve many-to-many relationships with heterogeneous data that sets up needs to:

Whether it’s a social network, payment networks, or road network you’ll find that everything is an interconnected graph of relationships. And when we want to ask questions about the real world, many questions are about the relationships rather than about the individual data elements.

In Neo4j, information is organized as nodes, relationships, and properties.

Nodes are the entities in the graph.

Relationships provide directed, named, connections between two node entities (e.g. Person LOVES Person).

If you’d like to learn more about any of these, you can read more about Graph Data Modeling.

Neo4j is an open-source, NoSQL, native graph database that provides an ACID-compliant transactional backend for your applications that has been publicly available since 2007.

Neo4j is offered as a managed service via AuraDB. But you can also run Neo4j yourself with either Community Edition or Enterprise Edition. The Enterprise Edition includes all that Community Edition has to offer, plus extra enterprise requirements such as backups, clustering, and failover abilities. Neo4j is written in Java and Scala, and the source code is available on GitHub.

Neo4j is a native graph database, which means that it implements a true graph model all the way down to the storage level. The data isn’t stored as a "graph abstraction" on top of another technology, it’s stored just as you whiteboard it. This is important because it’s the reason why Neo4j outperforms other graphs and stays so flexible. Beyond the core graph, Neo4j provides what you’d expect out of a database; ACID transactions, cluster support, and runtime failover. This stability and maturity is why it’s been used in production scenarios for large enterprise workloads for years.

What makes Neo4j the easiest graph to work with?

Neo4j is used today by thousands of startups, educational institutions, and large enterprises in all sectors including financial services, government, energy, technology, retail, and manufacturing. From innovative new technology to driving businesses, users are generating insights with graph, generating new revenue, and improving their overall efficiency.

Learn more about different use cases and companies using them in the video below.