A Year in Review: Welcome 2022 with ArangoDB.
Estimated reading time: 4 minutes
As the new year begins, It’s time to take a step back and reflect on 2021. 2021 was a big year for ArangoDB, and none of it would have been possible without the hard work and dedication of our team, as well as the continuous support from our community. This blog post recaps a few of our favorite moments from the last year and to get excited about what 2022 has in store for ArangoDB.
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A Guide to Putting Together a Virtual Conference
Estimated reading time: 7 minutes
Hello! I’m Cris Miranda, the community manager at ArangoDB, and I make sure ArangoDB has a vibrant, wholesome, and ever-growing community of amazing people. I want to share some tips and advice based on valuable lessons we’ve learned from our first-ever virtual developers’ conference.
In this short blog post, you’ll learn about how to avoid the common pitfall of ‘feature creep’ as well as gain tips on navigating virtual events platforms. I also teach you how you and your team can move together in synchronicity while keeping your goals as your guiding lighthouse. Lastly, I’ll teach you the best mindset to approach the world of rapidly changing live events. Alright, let’s get started!
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ArangoSync: A Recipe for Reliability
Estimated reading time: 18 minutes
A detailed journey into deploying a DC2DC replicated environment
When we thought about all the things we wanted to share with our users there were obviously a lot of topics to choose from. Our Enterprise feature; ArangoSync was one of the topics that we have talked about frequently and we have also seen that our customers are keen to implement this in their environments. Mostly because of the secure requirements of having an ArangoDB cluster and all of its data located in multiple locations in case of a severe outage.
This blog post will help you set up and run an ArangoDB DC2DC environment and will guide you through all the necessary steps. By following the steps described you’ll be sure to end up with a production grade deployment of two ArangoDB clusters communicating with each other with datacenter to datacenter replication.
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A Comprehensive Case-Study of GraphSage using PyTorchGeometric and Open-Graph-Benchmark
Estimated reading time: 15 minute
This blog post provides a comprehensive study on the theoretical and practical understanding of GraphSage, this notebook will cover:
- What is GraphSage
- Neighbourhood Sampling
- Getting Hands-on Experience with GraphSage and PyTorch Geometric Library
- Open-Graph-Benchmark’s Amazon Product Recommendation Dataset
- Creating and Saving a model
- Generating Graph Embeddings Visualizations and Observations
Community Notebook Challenge
Calling all Community Members! 🥑
Today we are excited to announce our Community Notebook Challenge.
What is our Notebook Challenge you ask? Well, this blog post is going to catch you up to speed and get you excited to participate and have the chance to win the grand prize: a pair of custom Apple Airpod Pros.
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Detecting Complex Fraud Patterns with ArangoDB
Introduction
This article presents a case study of using AQL queries for detecting complex money laundering and financial crime patterns. While there have been multiple publications about the advantages of graph databases for fraud detection use cases, few of them provide concrete examples of implementing detection of complex fraud patterns that would work in real-world scenarios.
This case study is based on a third-party transaction data generator, which is designed to simulate realistic transaction graphs of any size. The generator disguises complex financial fraud patterns of two kinds:
- Circular money flows: a big amount of money is going through different nodes and comes back to the source node.
- Indirect money transfers: a big amount of money is sent from source node to a target node over a multi-layered network of intermediate accounts.
Introducing ArangoDB 3.8 – Graph Analytics at Scale
Estimated reading time: 5 minutes
We are proud to announce the GA release of ArangoDB 3.8!
With this release, we improve many analytics use cases we have been seeing – both from our customers and open-source users – with the addition of new features such as AQL window operations, graph and Geo analytics, as well as new ArangoSearch functionality.
(more…)Entity Resolution in ArangoDB
Estimated reading time: 8 minutes
This post will dive into the world of Entity Resolution in ArangoDB. This is a companion piece for our Lunch and Learn session, Graph & Beyond Lunch Break #15: Entity Resolution.
In this article we will:
- give a brief background in Entity Resolution (ER)
- discuss some use-cases for ER
- discuss some techniques for performing ER in ArangoDB
Inside the Avocado Grove: From Canada to Germany and the Digital Marketing of Avocados
Estimated reading time: 8 minutes
My name is Laura, and I am responsible for digital marketing here at ArangoDB.
In the following post, I will dive into my own experience working at ArangoDB and how I ended up from Northern Ontario, Canada to work in Germany at a native multi-model graph database company. Are you interested in learning more about working abroad, working remotely, or diving into a new industry? This post covers all of the above topics.
(more…)Word Embeddings in ArangoDB
Estimated reading time: 12 minute
This post will dive into the world of Natural Language Processing by using word embeddings to search movie descriptions in ArangoDB.
In this post we:
- Discuss the background of word embeddings
- Introduce the current state-of-the-art models for embedding text
- Apply a model to produce embeddings of movie descriptions in an IMDb dataset
- Perform similarity search in ArangoDB using these embeddings
- Show you how to query the movie description embeddings in ArangoDB with custom search terms
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