Graph Analytics: Part 1

In my past 3 years as a Data Science professional, I have worked extensively with both RDBMS (Postgres) & Cassandra (NoSQL) but didn't get a chance to explore Graph databases. So, it's time to jump onto graph databases & how they can be integrated into different data science solutions. Consider this: Observe Google Maps for any city. A graph is basically a collection of Nodes (the landmarks) & edges(the roads). Nodes are connected (or may not be connected at all)to each other using the edges. Neo4j is the most popular database for analyzing graph data.