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Knowledge graphs are built on top of graph databases. While many users have some familiarity with graph databases, not everyone understands how and why these databases operate as they do. This can restrict how effective developers may be when creating data models and queries for graph databases, thus limiting their ability to make informed technology choices for data storage.

This talk describes the implementation of a complete graph database written in Clojure and ClojureScript. We will discuss how various stores address the needs of indexing and storage for graph data. We will also look at how queries are evaluated, including the important question of query optimizers, both in local storage, and for distributed systems.

These principles will be demonstrated at every stage with Asami: a Datomic-like graph database implementation that can run entirely within an application or in a web page. While the demonstration code of this talk will come from Asami, it will be compared and contrasted to other graph databases, including Datascript, Datomic, Mulgara and Jena.

Agenda:
6:00 - 7:00 PM - Networking & Snacks
7:00 - 8:00 PM - Paula Gearon's presentation

Bio:
In her 9th year of Clojure development, Paula likes to work in the most technical parts of a system building the infrastructure that lets other developers do their jobs. She has been the technical lead on several commercial and open source projects, with a focus on data storage and processing, and was a lead editor for the SPARQL standard for accessing RDF databases. When not coding, she does triathlons, cooks, helps her children with homework, and mentors and supports young members of Women Who Code. Originally from Australia, she currently lives with her family in Virginia, in the USA.

Location:
Stardog Office
2101 Wilson Boulevard Suite 800
Arlington, VA 22201

There is parking garage in the building and we are just across the street from the Courthouse Metro. There will be folks at the lobby doors letting you in and directing you to the right location as well.

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