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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.
More infoEstimated reading time: 4 minutes
Hello Community,
Welcome to the fourth ArangoDB newsletter of 2022. This month, we invite you to:
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.
More infoEstimated reading time: 4 minutes
Hello Community,
Welcome to the third ArangoDB newsletter of 2022. This month, we invite you to:
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.
More infoEstimated reading time: 4 minutes
Hello Community,
Welcome to the second ArangoDB newsletter of 2022.
You survived the first month of the year – congratulations! Why not take some time to enjoy a little 🥑 goodness, such as:
Estimated reading time: 15 minutes
We are proud to announce the GA 1.0 release of the ArangoDB-DGL Adapter!
The ArangoDB-DGL Adapter exports Graphs from ArangoDB, a multi-model Graph Database, into Deep Graph Library (DGL), a python package for graph neural networks, and vice-versa.
More info
Estimated reading time: 18 minute
We are proud to announce the GA 3.0 release of the ArangoDB-NetworkX Adapter!
The ArangoDB-Networkx Adapter exports Graphs from ArangoDB, a multi-model Graph Database, into NetworkX, the swiss army knife for graph analysis with python, and vice-versa.
More info
