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Data Model Questions /

Moderators: martimiz, Sean, Ed, biapar, Willr, Ingo, swaiba

Time Based Graph Data Modeling

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Community Member, 1 Post

6 June 2017 at 9:30pm

I have a data modeling question. The data that I have is basically nodes with relations to other nodes. Nodes have properties. Edges are directional and have properties. I am exploring if a Graph DB like Neo4j will be appropriate or not.

The doubt is because: The data that I have is time based. It changes on the basis of time, and I need to keep track of the historical data as well. For example, I should be able to query:

What was the graph like on a particular date?
Who all did a given node depend on at a particular time?
What were the properties of the edge between two given nodes at a particular time?
I searched but couldn't find a satisfactory resource where I could understand how time can be factored into a Graph DB. Do you think my requirement can be inherently met using a Graph DB? Is there an example/resource/article which describes this for Neo4j or any other graph db?

I want to make sure that the database is scalable to about 100K nodes, and millions of edges. I am optimizing for time over space.