Hilbert Curves & Polyhedrons for Geo-Indexing | ArangoDB Blog 2012
Cambridge mathematician Richard R. Parker presents a novel algorithm he has developed using a Hilbert curve and Polyhedrons to efficiently implement geo-indexing.
AvocadoDB Memory Management & Consistency | ArangoDB Blog 2012
AvocadoDB uses AppendOnly memory-mapped files with frequent fsync. Derived data (indices, etc.) is stored in the main memory only. This article explains why that particular combination leads to high performance and consistent data at the same time―even in case of a system failure.
Classical database systems – a bulk of data and insufficient main memory
Put simply, there are three possible settings regarding databases:
- Setting 1: All data fits into the main memory.
- Setting 2: The complete data pool does not fit into the main memory all at once, but the main memory is large enough to store all the data accessed in an average time span.
- Setting 3: Even the sub-set of data accessed in an average time span is too large for the main memory.
Classical database systems had to cope with setting 3 because main memory was too expensive to store the majority of data.
Basically, classical database systems had to manage the main memory themselves. To manage all data sets that exceeded the capacity of the main memory they needed sufficiently intelligent algorithms which the system software couldn’t provide (i.e., to stream the data through main memory for full table scans).
Wanted: Python API Contributors for NoSQL Project | ArangoDB Blog 2012
ArangoDB 3.12 – Performance for all Your Data Models
Estimated reading time: 6 minutes
We are proud to announce the GA release of ArangoDB 3.12!
Congrats to the team and community for the latest ArangoDB release 3.12! ArangoDB 3.12 is focused on greatly improving performance and observability both for the core database and our search offering. In this blog post, we will go through some of the most important changes to ArangoDB and give you an idea of how this can be utilized in your products.
(more…)Advanced Fraud Detection in Financial Services with ArangoDB and AQL
Estimated reading time: 3 minutes
Advanced Fraud Detection: ArangoDB’s AQL vs. Traditional RDBMS
In the realm of financial services, where fraud detection is both critical and complex, the choice of database and query language can impact the efficiency and effectiveness of fraud detection systems. Let’s explore how ArangoDB – a multi-model graph database – is powered by AQL (ArangoDB Query Language) to handle multiple, real-world fraud detection scenarios in a much more seamless and powerful way compared to traditional Relational Database Management Systems (RDBMS).
(more…)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.
(more…)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
(more…)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.
(more…)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.
(more…)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:
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AvocadoDB: The Best NoSQL Database | ArangoDB Blog 2012
Our mission: projects are different, project requirements change. We want to offer with AvocadoDB a most universally applicable nosql database which can be used in a maximum number of different use cases. In buzzword bingo language: we want to become the MySql in nosql – without MySql’s annoyances of course ;-).
AvocadoDB’s Design Objectives | ArangoDB Blog 2012
Before we started programming the new open source NoSQL database, we reflected which design objectives to achieve or to drop. This article summarizes our considerations.
In a nutshell:
- Schema-free schemas with shapes: Inherent structures at hand are automatically recognized and subsequently optimized.
- Querying: ArangoDB is able to accomplish complex operations on the provided data (query-by-example and query-language).
- Application Server: ArangoDB is able to act as application server on Javascript-devised routines.
- Mostly memory/durability: ArangoDB is memory-based including frequent file system synchronizing.
- AppendOnly/MVCC: Updates generate new versions of a document; automatic garbage collection.
- ArangoDB is multi-threaded.
- No indices on file: Only raw data is written on hard disk.
- ArangoDB supports single nodes and small, homogenous clusters with zero administration.
Hello World! Introduction to ArangoDB | ArangoDB Blog 2012
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