Dev Days: Day 3 - ArangoDB

Dev Days: Day 3

Dev Days: Day 3

  October 20th, 2021 Schedule

7:00 AM – 8:00 AM PDT: Featured Community Talk

Lessons learned: Creating a complete ERP-System with ArangoDB ft. Richard Burkhardt

In 2017 we started to develop an ERP-System for a large-scale caterer from scratch. Our goal was to make it possible to let around 50k customers and around 300 employees interact with this system in a reactive way and without caching or any other performance tricks. We are happy that we found ArangoDB, but had to start without any experience. This talk will be about the mistakes, the experience, and the success story.

8:00 AM – 9:00 AM PDT: Fireside Chat

Going Above and Beyond with ArangoSearch with Chris Woodward

In this talk, we deep dive into ArangoDB’s built-in search engine ArangoSearch. We look at the underlying informational retrieval concepts that make ArangoSearch so powerful. We will see how to configure analyzers, set up Views, and how to perform federated full-text search queries across multiple collections.

9:00 AM – 10:00 AM PDT: Demos

Kubernetes Meets Graphs with Jörg Schad

Learn how Kube-Arango makes deploying and managing ArangoDB on Kubernetes a breeze.

AQL for eCommerce Analytics with Jackson Reimers

Showcasing various AQL queries to analyze an eCommerce dataset for common questions in retail.

10:00 AM – 11:30 AM PDT: Workshop with Limited Spots (Registration Separate)

ArangoSearch: Full Text Meets Graphs with Chris Woodward

11:30 AM – 1:00 PM PDT: Workshop with Limited Spots (Registration Separate)

Cluster: From Apprentice to Wizard with Kaveh Vahidepour


1:00 PM – 2:00 PM PDT: Featured Community Talk Leveraging the NoSQL multimodel ArangoDB as the sole DB for a calm text-based social publication platform + monitoring and alerting using Prometheus and Kibana. is a text-based social publication platform that aims at efficiently servicing millions of users. Here we introduce how we are using ArangoDB as the unique database for the project and will also show how we built a system of monitoring and alerting using Prometheus and Kibana.

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