Update: Evolving ArangoDB’s Licensing Model for a Sustainable Future

Estimated reading time: 7 minutes

Update: https://arangodb.com/2023/10/evolving-arangodbs-licensing-model-for-a-sustainable- future/

Last October the first iteration of this blog post explained an update to ArangoDB’s 10-year-old license model. Thank you for providing feedback and suggestions. As mentioned, we will always remain committed to our community and hence today, we are happy to announce yet another update that integrates your feedback.

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The world is a graph: How Fix reimagines cloud security using a graph in ArangoDB

‘Guest Blog’

Estimated reading time: 5 minutes

In 2015, John Lambers, a Corporate Vice President and Security Fellow at Microsoft wrote “Defenders think in lists. Attackers think in graphs. As long as this is true, attackers win.ˮ

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Reintroducing the ArangoDB-RDF Adapter

Estimated reading time: 1 minute

ArangoRDF allows you to export Graphs from ArangoDB into RDFLib, the standard library for working with Resource Description Framework (RDF) in Python, and vice-versa.

Back in December 2023, we (quietly) released ArangoRDF’s 0.1 distribution, which reworked
functionality to introduce a consistent RDF-to-ArangoDB & ArangoDB-to-RDF experience based
on the paper Transforming RDF-star to Property Graphs: A Preliminary Analysis of
Transformation Approaches
.

Our latest 0.9 release complements previous overhaul & restoration changes by increasing the
number of transformation cases covered, optimizing its codebase, and improving
documentation.

This blog post will provide a brief outline and links for the walkthrough of ArangoRDF as
demonstrated by the official Jupyter Notebook mentioned below.

In the notebook you will find the following use cases:

  1. ArangoDB to RDF
    • Via an ArangoDB graph
    • Via a set of ArangoDB Collections
    • Via a user-defined Metagraph
  2. RDF to ArangoDB
  3. Full Cycles
    • ArangoDB → RDF → ArangoDB
    • RDF → ArangoDB → RDF

We hope you enjoy the notebook, you can get started with it today on:
- GitHub
- Google Colab

As always we look forward to your feedback!

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Introducing ArangoDB’s Data Loader : Revolutionizing Your Data Migration Experience

Estimated reading time: 7 minutes

At ArangoDB, our commitment to empowering companies, developers, and data enthusiasts with cutting edge tools and resources remains unwavering. Today, we’re thrilled to unveil our latest innovation, the Data Loader, a game-changing feature designed to simplify and streamline the migration of relational databases to ArangoGraph. Let’s dive into what makes Data Loader a must-have tool for your data migration needs.

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How ArangGraphML Leverages Intel’s PyG Optimizations

Estimated reading time: 3 minutes

ArangoGraphML + Intel: Next-level Machine Learning Accelerated

ArangoDB and Intel have announced a groundbreaking partnership to enhance Graph Machine Learning (GraphML) using Intel’s high-performance processors. This collaboration, part of the Intel Disruptor Program, will seek to integrate ArangoDB’s graph database solutions with Intel’s Xeon CPU. This synergy promises to revolutionize data analytics and pattern recognition in complex graph structures, marking a new era in database technology and GraphML advancements.

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ArangoDB’s Exciting Updates: Introducing Our Developer Hub and GenAI Bots!

Estimated reading time: 3 minutes

At ArangoDB, our commitment to empowering developers and data enthusiasts with cutting-edge tools and resources is unwavering. In line with our commitment to “Graph Done Simple,” we are thrilled to unveil two groundbreaking additions to our arsenal that promise to revolutionize your experience with our multi-model graph database.

Developer Hub: Where Knowledge Meets Accessibility

We’ve always believed in the power of community-driven knowledge sharing, and we are proud to present our brand-new Developer Hub, accessible at developer.arangodb.com. This hub is a testament to our dedication to creating an ecosystem that empowers you with the knowledge and resources you need.

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Evolving ArangoDB’s Licensing Model for a Sustainable Future

Estimated reading time: 3 minutes

ArangoDB as a company is firmly grounded in Open Source. The first commit was made in October 2011, and today, we are very proud of having over 13,000 stargazers on GitHub. We believe that the ArangoDB community should be able to enjoy all of the benefits of using ArangoDB, and we have always offered a completely free community edition in addition to our paid enterprise offering.

With the evolving landscape of database technologies and the imperative need to ensure ArangoDB remains sustainable, innovative, and competitive, we’re introducing some changes to our licensing model. These alterations will help us continue our commitment to the community, fuel further development, and assist businesses in obtaining the best from our platform.
These alterations are based on changes in the broader database market.

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ArangoGraph Now Available on AWS Marketplace

Estimated reading time: 1 minute

Today we are excited to announce that ArangoGraph, the ArangoDB Managed Service, is available for purchase in the AWS Marketplace. With this announcement, ArangoGraph can now be purchased directly via both AWS and GCP.

The AWS Marketplace provides an extensive catalog of software solutions for users to easily explore, test, buy, and deploy on AWS. If you’re an AWS customer, here’s what this announcement means for you:

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Bridging Knowledge and Language: ArangoDB Empowers Large Language Models for Real-World Applications

Estimated reading time: 5 minutes

Understanding Large Language Models (LLMs) and Knowledge Graphs

Today, two very different technology concepts have become prominent in data analysis and predictive analytics: Knowledge Graphs and Large Language Models (LLMs). These domains each have their unique benefits, and influence the ways that we engage with and derive meaningful insights from constantly expanding and complex datasets.  They are like the Odd Couple – better together than on their own!

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Three Ways to Scale your Graph

Estimated reading time: 10 minutes

As businesses grow and their data needs increase, they often face the challenge of scaling their database systems to keep up with the increasing demand.

What happens when your single server machine is no longer sufficient to store your graph that has grown too large? Or when your instance can no longer cope with the increasing amount of user requests coming in?

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