ArangoGraph's best use case is relationship mapping, such as finding connections between entities like which user interacted with which product through which channels. Graph traversal queries make this extremely fast and intuitive. ArangoGraph changed the way our teams think about data. Instead of thinking in tables and rows, we started thinking in relationships and connections. This mental shift improved our overall data modeling approach across the entire project. The graph traversal features were transformative; finding second and third degree relationships between entities that would have required multiple complex SQL joins was simply solved with a straightforward AQL query in ArangoGraph. This directly improved our application's recommendation logic performance.
My main use case for ArangoGraph is to build a customer graph in order to create a relation between customer and end users. I connect all the user related data together between the orders that they made from the supplier and customers.
Find out what your peers are saying about ArangoDB, Microsoft, Amazon Web Services (AWS) and others in Database as a Service (DBaaS). Updated: August 2026.
With DBaaS, businesses can manage their databases without handling the underlying infrastructure. It offers scalability, reliability, and user-friendly interfaces, making it efficient for IT teams. DBaaS solutions streamline database management by minimizing administrative tasks. They empower organizations to swiftly scale operations and enhance their performance. Automation features reduce the need for manual intervention while ensuring high availability and seamless integration...
ArangoGraph's best use case is relationship mapping, such as finding connections between entities like which user interacted with which product through which channels. Graph traversal queries make this extremely fast and intuitive. ArangoGraph changed the way our teams think about data. Instead of thinking in tables and rows, we started thinking in relationships and connections. This mental shift improved our overall data modeling approach across the entire project. The graph traversal features were transformative; finding second and third degree relationships between entities that would have required multiple complex SQL joins was simply solved with a straightforward AQL query in ArangoGraph. This directly improved our application's recommendation logic performance.
My main use case for ArangoGraph is to build a customer graph in order to create a relation between customer and end users. I connect all the user related data together between the orders that they made from the supplier and customers.