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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.
(more…)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.
(more…)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.
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:
(more…)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!
(more…)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?
Read moreGraph and Entity Resolution Against Cyber Fraud
Estimated reading time: 4 minutes
With the growing prevalence of the internet in our daily lives, the risks of malware, ransomware, and other cyber fraud are rising. The digital nature of these attacks makes it very easy for fraudsters to scale by creating thousands of accounts, so even if one is identified, they can continue their attacks.
In this blog post, we will discuss how graph and entity resolution (ER) can help us battle these risks across different industries such as healthcare, finance, and e-commerce (for example, the US healthcare system alone can save $300 billion a year with entity resolution). You will also receive hands-on experience with entity resolution on ArangoDB.
Combat Fraud with Graph
Estimated reading time: 5 minutes
Fraud is one of the most significant issues facing businesses today. While companies have always faced fraud, detecting fraudulent activity has become even more challenging due to increased online transactions. Globally, fraud results in more than $3.7 trillion in annual losses (Murphy, 2022). Fraud comes in numerous forms, including but not limited to money laundering, identity theft, account takeover, and payment fraud. Due to the variety of ways companies can face fraud, they must have a system to protect themselves and their customers.
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