Skip to content 
Resources
White papers, webinars, courses, and other useful resources to start and expand your journey to Graph Done Right.
Data Sheets
Read this overview to learn more about the highest-rated Graph Database, including use cases and benefits of every edition of ArangoDB.
You’ll see why ArangoDB’s flexible, next-gen architecture is the choice for customers who need to scale beyond Neo4j, delivering unmatched performance and value.
Introducing ArangoDB Visualizer, the next-level graph exploration tool designed to transform the way you interact with complex datasets. Leveraging the advanced capabilities of ArangoDB, this professional-grade viewer offers unparalleled clarity and insight into your graph data. With an emphasis on user experience, it simplifies the discovery of intricate data relationships through intuitive, dynamic representations. Enhance your analytical processes with a platform built for efficiency, accuracy, and ease of use.
Perfect for teams transitioning to a more scalable platform, this migration toolkit provides everything you need to make the switch from Neo4j to ArangoDB with ease and confidence.
Unlock the full potential of GenAI with knowledge graphs, gaining context-rich insights and accuracy that take your AI-driven applications to new heights.
E-Books
Perfect for decision-makers, this objective Buyer’s Guide simplifies the process of selecting a graph database (which might not be ArangoDB), providing critical questions and evaluation criteria to help you find the best fit for your unique needs.
See how ArangoDB’s graph technology can reveal hidden patterns in your supply chain data, helping you achieve modernization, transparency, and greater operational efficiency.
Look under the covers to discover how graph databases like ArangoDB streamline relationship-based queries, enabling faster, more efficient insights without the complex joins of the traditional RDBMS.
Explore how AQL on ArangoDB outshines Cypher on Neo4j, with an in-depth, technical comparison that reveals key advantages and insights for optimizing graph database performance.
White Papers
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.
Unlock powerful GenAI capabilities with knowledge graphs, turning disorganized data into actionable insights for speed, accuracy, and relevance.
Discover why ArangoDB’s GraphRAG with Knowledge Graphs delivers richer, context-aware insights than traditional Vector RAG, transforming data relationships into actionable intelligence.
Look under the covers to discover how graph databases like ArangoDB streamline relationship-based queries, enabling faster, more efficient insights without the complex joins of traditional databases.
Discover how ArangoDB’s key differentiator - its multi-model approach combining graph, document, full-text search, geospatial, and key/value models - unlocks hidden insights and powers advanced applications, driving smarter decisions and scalable, cost-effective results.
Designed for data leaders, this whitepaper explains why ArangoDB is the ideal upgrade from relational databases, with scalability and versatility that enhance your data handling.
Discover how ArangoDB’s multi-model technology reveals hidden fraud patterns, helping organizations tackle a $3.7 trillion global issue with scalable, advanced detection methods.
Enterprise Knowledge Graphs (EKGs) have been on the rise and are incredibly valuable tools for harmonizing internal and external data relevant to an organization into a common semantic model to improve operational efficiency for the enterprise and competitive advantage for the business units. On the other hand, EKGs can be difficult to develop and sustain, suffer from scalability issues, and can be difficult for business units to consume.
This White Paper describes some of these challenges and how a flexible data representation of a multi-model graph can address them.
In this white paper, we explain the resilience concept of ArangoDB 3. When an application runs on multiple machines or cloud instances, the probability of a machine failure is no longer negligible. Thus, if you run distributed applications and you want to sleep well, these applications need to be fault tolerant or resilient.
We show that an ArangoDB cluster with 640 vCPUs can sustain a write load of 1.1M JSON documents per second which amounts to approximately 1GB of data per second, and that it takes a single short command and a few minutes to deploy such an 80 node cluster using the Mesosphere DCOS.
When it comes to choosing the right technology for a new project, it can often be challenging to define the exact right tools that will match set-up criteria from start to finish. In this white paper, we explain what a multi-model database is, including a use case based on aircraft fleet management.
Infographics
Read why according to G2, ArangoDB users rated higher than Neo4J. Graph database users rank ArangoDB higher for: Ease of Use, Meets Requirements, Ease of Admin, Query Language, Quality of Service, Ease of Doing Business.
With the FBI estimating that cybercrime costs Americans over $6 billion annually and the World Economic Forum predicting it could reach $10.5 trillion by 2025, it’s clear that cybersecurity is a crucial concern for companies of all sizes.
Graph databases provide inherent advantages in scenarios where complex, multi-level relationships between data need to be established and queried at scale for efficient decision-making. ArangoDB’s Graph Done Right approach addresses the challenges faced by organizations in managing interconnected data and empowering a growing number of data users.
This infographic highlights the benefits of using graph databases for network management in today’s complex enterprise networks. The use of graph databases for network management is explained through various capabilities, including troubleshooting network errors, analyzing capacity, cataloging assets, scaling IT operations, optimizing infrastructure design, and planning downtime. It emphasizes that graph databases have been primarily used by data scientists, developers, and architects but have extensive applications in network management. Learn more about the role that graph technologies will play in data innovations, with 80% of data innovations expected to use graph technologies by 2025.
In this demo, we will share how ArangoDB can be snapshotted with the ease of a single AP call.
Courses
Read this overview to learn more about the highest-rated Graph Database, including use cases and benefits of every edition of ArangoDB.
If you made your first steps with AQL, played around with a few queries and now want to speed things up a bit, this course is for you.
Lunch Break Sessions
The Graph and Beyond Lunch Break is a series of 10-15min videos about topics like Fraud Detection with ArangoDB, AQL for eCommerce Analytics, Graph Analytics and more.
Recent Webinars Recordings
Watch the Hacktoberfest 2020 Intro to Knowledge Graphs talk with Chris Woodward and the team from reKnowledge
Ewout Prangsma (ArangoDB ArangoGraph) and Ayal Rosenberg (WeBill.net) discuss the impact of a managed multi-model graph database on development efficiency.