You can now do graph analysis with PageRank, degree centrality, betweenness centrality, or any other algorithm on subgraphs without any additional adjustments. Before you had to create new query procedure. You can fire up a graph machine learning algorithm, such as Temporal graph networks and split the dataset inside the query to do training and validation without splitting the dataset programmatically. And last but not least, you can use your graphics card to run one of cuGraph's algorithms on subgraph in terms of seconds.

You can find the whole explanation in blog post [1] and you can checkout the code at Memgraph GitHub [2]. Furthermore you can check cuGraph's algorithms we have integrated [3]

I'd like to hear your feedback on our approach. Also if you have any general feedback, just write it in the comments :)

[1] https://memgraph.com/blog/how-we-designed-and-implemented-gr...

[2] https://github.com/memgraph/memgraph/

[3] https://memgraph.com/docs/mage/query-modules/cuda/cugraph