The ArangoDB-PyG Adapter exports Graphs from ArangoDB, the multi-model database for graph & beyond, into PyTorch Geometric (PyG), a PyTorch-based Graph Neural Network library, and vice-versa. | Continue reading
This article will highlight What is a graph, what is a graph database, different types of graph databases and graph database use cases. | Continue reading
Build a movie recommendation application with ArangoDB and PyTorch Geometric. | Continue reading
We are proud to announce the GA 1.0 release of ArangoDB Datasource for Apache Spark: a new generation Spark connector for ArangoDB. | Continue reading
Formatting, Syntax, Styling & Performance Tuning with an interactive tutorial | Continue reading
We are proud to announce the release of ArangoDB 3.8! With this release ArangoDB improves many use-cases analytics. | Continue reading
We are proud to announce the GA 1.0 release of the ArangoDB-DGL Adapter! | Continue reading
Learn more about the ArangoDB-Networkx Adapter, available now. | Continue reading
ArangoDB presents; Dev Days 2021. Featuring talks, fireside chats, workshops, and much more. Join us the week of October 18th through October 22nd and take part in the future of data science and machine learning. | Continue reading
What is our Notebook Challenge you ask? Well, this blog post is going to catch you up to speed and get you excited to participate and have the chance to win the grand prize: a pair of custom Apple Airpod Pros. | Continue reading
We are proud to announce the release of ArangoDB 3.8! With this release ArangoDB improves many use-cases analytics. | Continue reading
Today we’re announcing the introduction of Developer deployments as a beta feature on the Oasis platform. In this blog post, we’ll tell you what Developer deployments are, what you can do with them, what you should not do with them, and how to get started. | Continue reading
The new release includes many upgrades to work with graphs at scale and adds a bunch of new search capabilities including Fuzzy Search based on n-gram and Levenshtein | Continue reading
Together with my team, I took a deep dive into the available fuzzy search approaches and algorithms for quite a while, in order to find a performant solution for the various projects ArangoSearch gets used for. In this article, we will share our learnings and hope they are useful … | Continue reading
Some say graph databases do not scale (well). Because growing datasets lead to various performance issues. In this post we will take a look at the claims and how to solve issues in scale-up and scale-out scenarios | Continue reading
There are many things the global coronavirus pandemic crisis has shown us, but there are a few things that stand out. One of them is that the current vaccine and drug development process takes a lot of time. Some would even say too long for having the desired impact on containing … | Continue reading
ArangoML Pipeline, a flexible Metadata store which can be used with your existing ML Pipeline. It can be used as a simple extension of existing ML pipelines | Continue reading
ArangoDB 3.6 release comes with several significant performance improvements, enchancements in ArangoSearch and a brand new feature - OneShard. | Continue reading
Nothing performs faster than arangoimport and arangorestore for bulk loading or massive inserts into ArangoDB. However, if you need to do additional processing on each row inserted, this blog will help with that type of functionality. If the data source is a streaming solution (s … | Continue reading
Announcing ArangoDB Oasis – a fully-managed graph database, document, and key-value store, as well as a full-text search engine – in one place. | Continue reading
Running distributed databases on-prem or in the cloud is always a challenge. Over the past years, we have invested a lot to make cluster deployments as simple as possible, both on traditional (virtual) machines (using the ArangoDB Starter) as well as on modern orchestration syste … | Continue reading
Over the past two years, many of our customers have productionized their machine learning pipelines. Most pipeline components create some kind of metadata which is important to learn from. This metadata is often unstructured (e.g. Tensorflow’s training metadata is different from … | Continue reading
Over the past two years, many of our customers have productionized their machine learning pipelines. Most pipeline components create some kind of metadata which is important to learn from. This metadata is often unstructured (e.g. Tensorflow’s training metadata is different from … | Continue reading
This is a story of an excursion to the bottom of a deep rabbit hole, where I discovered a foot gun in gcc‘s libgcc. The investigation has cost me several days and I hope that by writing this up I can entertain others and save them the journey. TL;DR If a C++ application is compil … | Continue reading
With this new release we didn’t wait until Christmas again 🙂 No seriously, we are super excited to share the latest upgrades to ArangoDB which are now available with ArangoDB 3.5. With the fast-growing team, we could build many new and long-awaited features in the open-so … | Continue reading
On ArangoDB blog you will find all latest info, interesting discoveries and projects related to the NoSQL multi-model database. | Continue reading
With this new release we didn’t wait until Christmas again 🙂 No seriously, we are super excited to share the latest upgrades to ArangoDB which are now available with ArangoDB 3.5. With the fast-growing team, we could build many new and long-awaited features in the open-so … | Continue reading
In this webinar the presenters will showcase a variety of query options you have with a native multi-model database like ArangoDB. | Continue reading
In this Graphs of Game of Thrones webinar we will leverage graph and multi-model representations of GoT to recollect the events in prior seasons. | Continue reading
In this webinar, we discuss how we can use Kubernetes to build an end-to-end recommender system with ArangoDB and Kubernetes. | Continue reading
Sharding with ArangoDB: Distributed, clustered databases are, as far as one can tell right now, the future. Clustering implies two new degrees of freedom. | Continue reading
Run multiple versions of ArangoDB alongside each other on the same machines by using the new `.tar.gz` binary distribution of ArangoDB | Continue reading
ArangoDB is an easy to use mostly memory, high performance, open source NoSQL database with a unique combination of features. | Continue reading
When using a database it is also important to explore how it behaves once it reaches system bottlenecks, or which KPIs it can achieve in your benchmarks | Continue reading
It has been a few months since we first released the Kubernetes operator for ArangoDB and started to brag about it. Since then, quite a few things have happened. For example, we have done a lot of testing, fixed bugs, and by now the operator is declared to be production ready for … | Continue reading
ArangoDB 3.4: The next big step forward with over 40 new features, improvements and optimizations including ArangoSearch, GeoJSON and Streaming Cursor. | Continue reading
The ability to see your data from various perspectives is the idea of a multi-model database. Having the freedom to combine these perspectives into a single query is the idea behind native multi-model in ArangoDB. Extending this freedom is the main thought behind the release of A … | Continue reading
nihil novi nisi commune consensu nothing new unless by the common consensus – law of the polish-lithuanian common-wealth, 1505 A warning aforehand: this is a rather longish post, but hang in there it might be saving you a lot of time one day. Introduction Consensus has its etymol … | Continue reading
For ArangoDB 3.4 we already added 100,000 lines of code, happily deleted 50,000 lines and changed over 13,000 files until today. We merged countless PRs, invested months of problem solving, hacking, testing, hacking and testing again and are super excited to share the feature com … | Continue reading
Some graph database vendors propagandize index-free adjacency for the implementation of graph models. There has been some discussion on Wikipedia about what makes a database a graph database. These vendors tried to push the definition of index-free adjacency as foundation of grap … | Continue reading
We were in search for some C++ reader/writer locks implementation that allows a thread to acquire a lock and then optionally pass it on to another thread. | Continue reading
Kubernetes ArangoDB Operator 0.0.1 release - an ArangoDB Kubernetes integration development and how to try it out by running stateful cluster deployments in 5min | Continue reading
This article on static binaries describes how to generate a completely static binary for a complex C++ application which runs on all variants of Linux without any library dependency. | Continue reading
This article shows how we use tools and tricks from persistent data structure literature and allow time traveling in the graph database part of ArangoDB | Continue reading