Archive for the ‘ArangoDB’ Category

The Computer Science behind a modern distributed data store

Thursday, December 7th, 2017

From the description:

What we see in the modern data store world is a race between different approaches to achieve a distributed and resilient storage of data. Every application needs a stateful layer which holds the data. There are at least three necessary ingredients which are everything else than trivial to combine and of course even more challenging when heading for an acceptable performance.

Over the past years there has been significant progress in respect in both the science and practical implementations of such data stores. In his talk Max Neunhöffer will introduce the audience to some of the needed ingredients, address the difficulties of their interplay and show four modern approaches of distributed open-source data stores.

Topics are:

  • Challenges in developing a distributed, resilient data store
  • Consensus, distributed transactions, distributed query optimization and execution
  • The inner workings of ArangoDB, Cassandra, Cockroach and RethinkDB

The talk will touch complex and difficult computer science, but will at the same time be accessible to and enjoyable by a wide range of developers.

I haven’t found the slides for this presentation but did stumble across ArangoDB Tech Talks and Slides.

Neunhöffer’s presentation will make you look at ArangoDB more closely.

New Graph Visualisation [ArangoDB]

Monday, October 7th, 2013

New Graph Visualisation

From the post:

Are you storing Graphs in ArangoDB?
Ever wondered how exactly your data looks like?
Do you want to visually explore and maintain your Graph data?

We have a solution for you!

With ArangoDB 1.4 we ship an additional tab in the Administration Interface called “Graphs”. In this tab you can load your graph data and start exploring it visually. After you have defined the collections where your data is stored you can search for a start vertex by defining an attribute-value pair contained in it, or you can start from any random vertex. The new interface will then offer you the means to explore the graph by loading child vertices (SPOT) and you can configure the interface to display labels on your nodes and to draw nodes with different content in different colors as shown in the screenshot.

New visualization capabilities are always welcome!

The screen shots are impressive. How does it work for you?


Saturday, February 23rd, 2013


While looking for more information on Arango-DB, I stumbled across this collection of graph data sets:

Brief descriptions: ArangoDB-Data

Storing and Traversing Graphs in ArangoDB

Saturday, February 23rd, 2013

Storing and Traversing Graphs in ArangoDB by Frank Celler.


In this session we will use bibliographic data as an example of a large data-set with graph structure. In order to investigate this structure the data is imported into the multi-model database ArangoDB. This database allows to investigate and access the underlying graph: A query language gives you access to basic path structure. Graph traversals written in JavaScript allow you to explore that graph in-depth. Finally, a library of graph algorithms is available to look for hot-spots and the like.


ArangoDB supports its own query language as well as Gremlin.

Interesting for its use of JavaScript to explore the graph.

BTW, ArangoDB home.


Wednesday, December 12th, 2012


From the webpage:

A universal open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient sql-like query language or JavaScript/Ruby extensions.

Design 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.

I have mentioned this before but ran across it again at: An experiment with Vagrant and Neo4J by Patrick Mulder.

“AvocadoDB” becomes “ArangoDB”

Monday, May 28th, 2012

“AvocadoDB” becomes “ArangoDB”

From the post:

to avoid legal issues with some other Avocado lovers we have to change the name of our database. We want to stick to Avocados and selected a variety from Mexico/Guatemala called “Arango”.

So in short words: AvocadoDB will become ArangoDB in the next days, everything else remains the same. 🙂

We are making great progress towards version 1 (deadline is end of May). The simple query language is finished and documented and the more complex ArangoDB query language (AQL) is mostly done. So stay tuned. And: in case you know someone who is a node.js user and interesting in writing an API for ArangoDB: let me know!

We will all shop with more confidence knowing the “avocado” at Kroger isn’t a noSQL database masquerading as a piece of fruit.

Another topic map type issue: There are blogs, emails (public and private), all of which refer to “AvocadoDB.” Hard to pretend those aren’t “facts.” The question will be how to index “ArangoDB” so that we pick up prior traffic on “AvocadoDB?”

Such as design or technical choices made in “AvocadoDB” that are the answers to issues with “ArangoDB.”