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Deploying and Securing an ArangoDB Cluster Using Docker
Introduction Deploying a distributed database securely can be challenging, but Docker simplifies the process. This guide walks you through setting up a three-node ArangoDB cluster using Docker and Docker Compose. I’ll also cover essential security measures, including authentication, TLS encryption, and automated backups. Before You Begin Create a Folder: Create a dedicated folder on your…
Legal and Compliance challenges in modern finance and how ArangoDB plus GraphRAG solves them
Estimated reading time: 4 minutes In today’s financial sector, staying compliant isn’t just about keeping up – it’s about keeping your organization safe, agile, and ahead of the competition. Every week new sanction headlines, revised regulations, and internal policy updates flood your compliance teams. These aren’t just bulletins; they’re pressure points. Buried inside government websites,…
Deploying ArangoDB on Kubernetes and customizing settings
Estimated reading time: 6 minutes Introduction Deploying an ArangoDB cluster on Kubernetes is a straightforward process thanks to the ArangoDB Operator, a powerful tool that simplifies the deployment, management, and scaling of ArangoDB clusters in a Kubernetes environment. In this post, we’ll walk you through the steps to quickly deploy an ArangoDB cluster on Kubernetes,…
From Sensor Noise to Strategic Insights: How ArangoDB and GraphRAG are Reinventing IoT for Smart Manufacturing
Estimated reading time: 7 minutes The modern manufacturing floor hums not just with machines, but with data as well. From predictive maintenance and energy monitoring to quality control and supply chain automation, IoT devices now generate terabytes of time-series and event data on a daily basis. But here’s the reality: Most of that data goes…
Integrating ArangoDB with Kubernetes for Seamless Deployment
Estimated reading time: 6 minutes Are you a database architect or DevOps architect tasked with deploying modern databases like ArangoDB on Kubernetes? Kubernetes, with its robust orchestration capabilities, provides a solid foundation for managing containerized workloads, ensuring reliability and adaptability for database deployments. In this post, we’ll guide you through the process of deploying ArangoDB…
ArangoDB’s GraphRAG Transforms Healthcare Data Management
Estimated reading time: 7 minutes Healthcare Data Challenges Healthcare organizations across the spectrum-from large hospital systems to payers to individual providers-face unprecedented IT challenges. These include siloed information systems, complex regulatory requirements, and rapidly evolving clinical research. Add fast-growing patient expectations for personalized care, and one can relate to how challenging all this is. Traditional…
The Transformative Power of ArangoDB GraphRAG in Genomics-Driven Personalized Medicine
Estimated reading time: 7 minutes Introduction Personalized medicine is a truly disruptive innovation in healthcare. Medical treatment can now pivot from mass-market, standardized care models to custom-made, client-centric solutions. For example, healthcare providers can now offer precision-targeted therapeutic products and services using individual genetic data and lifestyle metrics. And this shift would drive improved patient…
Benchmark Results – ArangoDB vs. Neo4j : ArangoDB up to 8x faster than Neo4j
Introduction This document presents the benchmark results comparing the ArangoDB’s Graph Analytics Engine (GAE) against Neo4j. The GAE is just one component of ArangoDB’s Data Science Suite. This reproducible benchmark aims to provide a neutral and thorough comparison between the two databases, ensuring a fair and unbiased assessment. We use the wiki-Talk dataset, a widely…
Vector Search in ArangoDB: Practical Insights and Hands-On Examples
Vector search is gaining traction as a go-to tool for handling large, unstructured datasets like text, images, and audio. It works by comparing vector embeddings, numerical representations generated by machine learning models, to find items with similar properties. With the integration of Facebook’s FAISS library, ArangoDB brings scalable, high-performance vector search directly into its core,…
Some Perspectives on HybridRAG in an ArangoDB World
Introduction Graph databases continue to gain momentum, thanks to their knack for handling intricate relationships and context. Developers and tech leaders are seeing the potential of pairing them with the creative strength of large language models (LLMs). This combination is opening the door to more precise, context-aware answers to natural language prompts. That’s where RAG…