Talk in English - US at Lone Star PHP 2017
View Slides: https://github.com/michaelmoussa/talks/tree/master/intro-to-graph-databases-with-neo4j/lonestar2017
Short URL: https://joind.in/talk/5b436 (QR-Code (opens in new window))
Graph databases are all the rage these days, but the ideas they’re built upon are hundreds of years old. After a brief look at the history of graph theory and its practical applications in Computer Science, we’ll dive right into Neo4j - the world’s most popular graph database! Learn the differences between a graph database like Neo4j and your traditional RDBMS. See how to model your application’s domain using the new concepts available to you and how to query your graphs using Neo4j’s intuitive query language, Cypher. After this talk, you’ll agree that (Neo4j)-[:IS]->(Awesome) and be excited to use it in your next web application!
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Really good intro to graph databases and the query language. In just 50 minutes, Michael took me from almost zero knowledge of graph database use and structure to feeling comfortable enough to start working on adding graph database functionality to some of my personal projects. Thanks for the great talk!
Excellent introduction to graph databases in general and neo4j specifically. I appreciated Michael's example of visualizing a query as an actual set of nodes and edges. Lots of great resources at the end. This was a perfect introductory session. Thank you!
Really enjoyable talk, in depth coverage of the subject with a great level of technical detail. Engaging presentation and strong slide deck.
Dived into cypher a bit too quickly for most in the room to keep up with which led to some extended Q&A sessions halfway through the slide deck. @Michael: it might have been more effective to move more slowly with a bit more room for questions on some of the cypher introductory slides as the syntax is pretty foreign to me (and I assume most in the room). While I realize that a graph db vs SQL is apples vs oranges, it may help to present cypher with corresponding SQL queries where applicable.
I would have enjoyed some context on algorithmic complexity (this runs in 30 ms FOR SMALL DATASETS) and some examples which demonstrated nodes having unique attributes, as these are some of the features (and limitations) of a graph database, no?
Great presentation, well put together slides.