Estimated reading time: 4 minutes
Welcome to the fifth ArangoDB newsletter of 2021!
In this edition, we are excited to share:
- An upcoming webinar about ArangoDB 3.8
- The latest blog post in our ArangoML series
- Our next Lunch Break spotlighting Fuzzy Search
- Our growing avocado grove (aka we are hiring!)
We hope you enjoy it!
Webinar: ArangoDB 3.8 – Analytics at Scale
The ArangoDB 3.8 GA release is nearly here! We’re particularly excited about ArangoDB 3.8 as we’re doubling down on our capabilities to power analytics at scale – especially in graph and ArangoSearch.
Join our CTO, Jörg Schad, Ph.D., as well as Chris Woodward, Developer Relations Engineer, at this webinar to learn more about ArangoDB 3.8 and the roadmap for upcoming releases. New features discussed will include:
- AQL window operations
- Weighted Graph Traversal
- ArangoSearch Pipeline & AQL Analyzers
- Enhanced Geo support in ArangoSearch
- And many more!
Tuesday, June 22nd 2021 – 10:00am PDT / 1:00pm EDT / 7:00pm CEST
ArangoML Blog Series: Intro to NetworkX Adapter
This post is the fifth in a series of posts introducing ArangoML features and tools. It introduces the NetworkX adapter, which makes it easy to analyze your graphs stored in ArangoDB with NetworkX.
In this post, we:
- Briefly introduce NetworkX
- Explore the IMDB user rating dataset
- Showcase the ArangoDB integration of NetworkX
- Explore the centrality measures of the data using NetworkX
- Store the experiment with arangopipe
Graph & Beyond Lunch Break #11: Fuzzy Search
When dealing with real-world text retrieval, we often not only care about exact matches to our search phrase but need to consider for example typos or alternative spellings.
“Fuzzy search” is an umbrella term referring to a set of algorithms for such approximate matching. Usually, such algorithms evaluate some similarity measure showing how close a search term is to the items in a dictionary. Then, a search engine can make a decision on which results have to be shown first.
In this Lunch Break, we will take a look at different similarity measures and show how fuzzy search works in ArangoDB.
Register here ->
Where else can you find ArangoDB?
- June 9: AI@Enterprise Summit – Production-grade ML Pipelines – From Data To Metadata
- June 11: AI@Enterprise Summit – Building and Operating an Open Source Data Science Platform
From the Avocado Grove: We’re Hiring!
Team Avocado is continuing to grow! We have 20+ open positions (almost all fully-remote) on our website across Engineering, Product Management, Sales, and Recruiting. Today we’d like to introduce you to Sachin Sharma, who joined us recently as a machine learning research engineer.
As a Machine Learning Research Engineer at ArangoDB, Sachin aims to build intelligent products using thorough research and engineering in the area of graph machine learning. He is an AI enthusiast who has conducted research in the areas of Computer Vision, NLP, and Graph Neural Networks at DFKI (German Research Centre for AI) during his academic career. Sachin also worked on building Machine Learning pipelines at Define Media Gmbh where he worked as a Machine Learning Engineer and Scientist. You can reach Sachin through our ArangoDB Community Slack @sachin.arangodb.
Would you like to join Team Avocado? Check out our open positions here.
ArangoDB recognized as Leader on G2
We couldn’t be more thrilled to be recognized by our users as a Graph Database Leader on G2 Crowd.
Are you happy with how things are going with ArangoDB so far, and have a few minutes to spare? Then take a break from coding and write a review about your experience on G2.
We hope you enjoyed our latest news!
Until next time 🖖
The ArangoDB Team