Lunch Sessions

ArangoDB Graph & Beyond Lunch Break

In order to keep in better touch with our community, we invite you to join us for our ‘Graph & Beyond’ lunch break series. 

Every Wednesday we present you with a new 10-15min talk to learn more about ArangoDB – different use cases, new features we’re working on – delivered directly to your inbox. Grab some lunch, settle in your favorite chair, and watch a talk filled with practical examples for ArangoDB.

#5 – AQL Query Performance Optimization 101 (Part I)

  March 10th, 2021 – 12pm

This is Part 1 of 2 Lunch Break sessions covering the basics of AQL query performance optimization. Jan Steemann will check if and how indexes can help AQL query performance, and how to set up the indexes so that they help most.

#6 – AQL Query Performance Optimization 101 (Part II)

  March 24th, 2021 – 12pm

This is Part 2 of the Lunch Break sessions covering the basics of AQL query performance optimization. This Lunch Break session covers AQL query performance optimizations for cluster setups. It is a follow-up session to the AQL query performance optimization session from 2 weeks earlier.

Previous Graph & Beyond Lunch Sessions

View our recorded videos of the Graph & Beyond Lunch Sessions.

#1 – Fraud Detection with ArangoDB

We are going to use the multi-model graph capabilities within ArangoDB to identify fraud patterns (as used for money laundering) in financial datasets and catch some bad guys! Jackson Reimers will show various fraud patterns and how to detect them, using the ArangoDB graph visualizer.

#2 – ArangoSearch: Where Full-Text Search and Graphs Meet

In this Graph and Beyond Lunch session we will cover ArangoSearch, the full-text search engine natively integrated into ArangoDB. Chris Woodward will give an overview of how you can combine a wide range of search queries (e.g., phrase, proximity, or range), ranking (e.g., BM25 or TFIDF algorithms) and ArangoDB’s other data models (e.g., graph or document).

#3 – AQL for eCommerce Analytics

During this Lunch Session we will showcase various AQL queries to analyze an eCommerce dataset for common questions in retail, like:

  • What products are offered?
  • Where are they located in my store?
  • Which are the best selling products?
  • What can the data tell me about shopper purchasing behaviors?

#4 – Graph Analytics with ArangoDB

In this Graph & Beyond Lunch Session you learn about Graph Analytics with ArangoDB. We will take a short look at different graph algorithms such as Community Detection, Centrality Measures, and Recommendation, but also discuss challenges of scaling such analytics to enterprise use cases.

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