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Introducing the ArangoDB-PyG Adapter

Introducing the ArangoDB-PyG Adapter

00ArangoML, General, Graphs, how to, Machine LearningTags: , , , ,

Estimated reading time: 10 minutes

We are proud to announce the GA 1.0 release of the ArangoDB-PyG Adapter!

The ArangoDB-PyG Adapter exports Graphs from ArangoDB, the multi-model database for graph & beyond, into PyTorch Geometric (PyG), a PyTorch-based Graph Neural Network library, and vice-versa.

On July 29 2022, we introduced the first release of the PyTorch Geometric Adapter to the ArangoML community. We are proud to have PyG as the fourth member of our ArangoDB Adapter Family. You can expect the same developer-friendly adapter options and a helpful getting-started guide via Jupyter Notebook, and stay tuned for an upcoming Lunch & Learn session!

This blog post will serve as a walkthrough of the ArangoDB-PyG Adapter, via its official Jupyter Notebook.

More info

What is a Graph Database?

00ArangoML, Data Science, Future-of-nosql, General, Machine Learning, PublicationTags: , ,

Estimated reading time: 10 minutes

Introduction

Graphs occur everywhere in everyday life: your network of friends, the network of roads you drive on, and the supply chain of factories, ships, and roads that brought you the device you’re reading this on. While it might be easy to connect the dots on how most things can be shown as a graph, what makes a database a graph database? That is the question you will have the answer to in this blog post, but to put it simply: a graph consists of nodes, edges, and properties representing the relationships within data.

In this article, we will discuss:

  • What is a graph?
  • What is a graph database?
  • Different types of graph databases.
  • Graph database use cases.
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data-science-personas-banner

Who’s Who in Data Science

00ArangoML, Data Science, Future-of-nosql, General, Machine Learning, PublicationTags: , , , , , ,

Estimated reading time: 10 minutes

Multiple data science personas participate in the daily operations of data logistics and intelligent business applications. Management and employees need to understand the big picture of data science to maximize collaboration efforts for these operations. This article will highlight the specialized roles and skillsets needed for the different data science tasks and the best tools to empower data-driven teams. You will come away from this article with a better understanding of how to support your own data science teams, and it is valuable for both managers and team members alike.

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recommendMovies

Integrate ArangoDB with PyTorch Geometric to Build Recommendation Systems

00ArangoML, General, Graphs, how to, Machine LearningTags: , , , ,

Estimated reading time: 20 minutes

In this blog post, we will build a complete movie recommendation application using ArangoDB and PyTorch Geometric. We will tackle the challenge of building a movie recommendation application by transforming it into the task of link prediction. Our goal is to predict missing links between a user and the movies they have not watched yet.

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Apache Spark

Introducing the new ArangoDB Datasource for Apache Spark

00General, Releases

Estimated reading time: 8 minutes

We are proud to announce the general availability of ArangoDB Datasource for Apache Spark: a new generation Spark connector for ArangoDB.

Nowadays, Apache Spark is one of the most popular analytics frameworks for large-scale data processing. It is designed to process in parallel data that is too large or complex for traditional databases, providing high performances by optimizing query execution, caching data in-memory and controlling the data distribution.

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Introducing ArangoDB 3.9 – Graph Meets Analytics

00General, Releases

Estimated reading time: 4 minutes

We are proud to announce the GA release of ArangoDB 3.9!

Congrats to the team and community for the latest ArangoDB release 3.9! ArangoDB 3.9 is focused on extending the capabilities of advanced Analytics and especially at scaling Graph use cases even further. In the remainder of this blog post, we will dive further into some of the features including Hybrid SmartGraphs, new AQL functions, new ArangoSearch Analyzer, and various other performance and user experience improvements.

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