We have the Ne4j graph database running and the Cypher query ready to get the recommendation for every drink. We will need an Apollo server running in front of it to enable graphQL. GatsbyJs will connect to that graphQL endpoint during the build time to query for the recommended/similar drinks while building each drink’s detail page.
A recommendation engine can give site visitors an opportunity to discover the most relevant content on the site depending on the page user is browsing. A content publisher or a store can benefit from extra views/exposure or upselling.
Hello internet, I decided to write this up after presenting a talk about it to my colleagues at Inviqa recently. I will try to walk you through this mindblowing journey of modeling your data from scratch to building a graphQl API, to consuming the API and then serving it in a ReactJs app.
When you are setting up your Neo4j server and you can’t have access to Neo4j Browser, mostly if you are using AWS EC2 or some remote system and don’t want to expose those 7474 7687 ports, To set your initial password via command line do the following delete dbms/auth file from your neo4j data directory sudo […]
