
I wrote an introductory guide to graph tech - akashtndn
https://towardsdatascience.com/traversing-the-land-of-graph-computing-and-databases-5cbf8e8ad66b
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akashtndn
Hi HN,

Graph theory had fascinated me as a student. On my first job, I'd briefly
worked with Neo4j, a graph database, as part of a proof-of-concept project. At
my current gig, I've had the opportunity to delve deep into the world of graph
tech, especially databases, over the last one year.

Graph-like data models have been around since forever but their mainstream
promise is relatively new. A resource which helped me understand the
historical as well as fundamental aspects when starting out was the amazing
book, "Designing Data Intensive Applications" by Martin Kleppmann. There also
exist various resources academic and industry resources around graph tech. But
piecing them together to get a holistic picture to evaluate potential use-
cases has been an arduous process, to say the least. Hence, I wrote this
introductory piece to help anyone interested get started. I'd given a talk on
the same topic at PyCon Italy
([https://www.youtube.com/watch?v=t0Ra8G8gD-w](https://www.youtube.com/watch?v=t0Ra8G8gD-w)).
I plan to write more on related topics.

