Powered by a native graph database, Neo4j stores and manages data in its more natural, connected state, maintaining data relationships that deliver lightning-fast queries, deeper context for analytics, and a pain-free modifiable data model.
Neo4j is the most popular graph data store available today. It leverages graph technologies to help build modern high-performing applications, but it does not have any native multi-tenant support. However, you may have decided to build out your multi-tenant application and that Neo4j is the right graph data store to fit your needs. In any multi-tenant system, the trick (from a data-store side) really comes down to how to isolate one tenant’s data (physically or logically) from another tenant’s.
“Jeez, I’m out of it for a little while, everyone gets delusions of grandeur!” That’s what Han Solo said after being frozen in carbonite. I’ve been solving data problems for customers the last year and a half and am now getting back in graph DBMSs. We took a nice look at Titan last week, can’t wait to play with that some more. I’m going to give a bit of the same to Neo4j. All of this as prep for my talk at GraphDay 2016 in Austin, TX.
In this second post we look at how the application’s graph data fit into a leading graph database: Neo4j. Quite well actually.
