We would like to share one of the latest use cases we have recently performed at Sparsity Technologies with DEX.
We have created a DEX graph loading all tweets made from June to December 2009, with a total of more than 476M tweets and 1.2 billion follower relations.
The resulting graph has 655M nodes belonging to 4 different types: users, tweet, hashtag and url. Former nodes have relations such as retweet, follows or references making a total of 2.2 billion edges present in the graph. Nodes and edges have a total of 1.6 billion attributes. Twitter objects make a final 4.5 billion DEX graph database.
See the resulting schema:
The loading was made in a Linux machine with 64GB RAM and a single CPU and the resulting graph database has 192GB; this is 3 times the available memory.
Resulting graph is ready to be queried. If you were wondering if social networks such as twitter or facebook could take advantage of graph databases, we are positive this test contributes to the exploration of this interesting scenario.
Questions like “Is it reasonable to work with such a big graph?” or “How long queries to the graph will take?” arise. We’ll return with more information.