The main difference between graph databases and triple stores is how they model the graph. In a triple store (or quad store), the data tends to be very atomic. What I mean is that the “nodes” in the graph tend to be primitive data types like string, integer, date, etc. Relationships link primitives together, and … Read more
For general querying, Cypher is enough and is probably faster. The advantage of Gremlin over Cypher is when you get into high level traversing. In Gremlin, you can better define the exact traversal pattern (or your own algorithms) whereas in Cypher the engine tries to find the best traversing solution itself. I personally use Cypher … Read more
There actually is conceptual reasoning behind both styles. Wikipedia on the relational model and graph databases gives good overviews of this. The primary difference is that in a graph database, the relationships are stored at the individual record level, while in a relational database, the structure is defined at a higher level (the table definitions). … Read more
I used a graph database in a previous job. We weren’t using neo4j, it was an in-house thing built on top of Berkeley DB, but it was similar. It was used in production (it still is). The reason we used a graph database was that the data being stored by the system and the operations … Read more
My current project actually. Storing 18,000 objects in a normalised structure: 90,000 rows across 8 different tables. Took 1 minute to retrieve and map them to our Java object model, that’s with everything correctly indexed etc. Storing them as key/value pairs using a lightweight text representation: 1 table, 18,000 rows, 3 seconds to retrieve them … Read more