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The first beta release of ArangoDB 2.8 is available for download now, adding Array Indexes and Graph Traversals in AQL. Please try the new version, report bugs on Github and provide us your valuable feedback.
Check out the latest blog posts to get some more background about performance improvements and added features. Read more
Max wrote an inspiring article about graphs in data modeling on Medium, packed with his own thoughts – “to sort out some things in my brain” (Max).
He asks and answers the question: Are graphs and graph databases useful in data modeling, and if so, for what and under which circumstances?
In his article, he goes all the way down from the theoretical approach of what is a graph? towards storing a graph in different storage models (RDBMS, document store and graph databases) to querying a graph and finally to his personal conclusion. More info
After defining a graph and filling it with some vertices and edges (see part 1), the time has come to retrieve information out of the graph.
Please take a look at the defined graph operations of ArangoDB. These will be the base for our next examples. (Yes, there may be other ways to get the results, this post does not claim completeness!)
We will start with some easy stuff and then smoothly advance in complexity.
Question: “How many edges are defined within the graph?”
This post is outdated, please see more recent infos below.
Please see a technical article about our current Pregel integration in our blog, details about the various Pregel algorithms ArangoDB supports in our documentation and a tutorial about Community Detection with real data in our training center.
Ever since Google introduced Pregel as a system for large-scale graph processing we thought of a way how to enable this feature in ArangoDB. So we set up an ArangoDB cluster, created some huge graphs and started evaluating the concept. We came up with a new ArangoDB module (called pregelRunner) that enables the user to write own algorithms, pass them to ArangoDB and have them executed in a Pregel-like fashion.
This means that the user’s algorithm is executed step wise on each server in the cluster in parallel for all its local vertices. In each step the vertices can send messages to each other to distribute information. These messages can be received by the other vertex in the next step. The algorithm terminates when there are no more active vertices left and no message has been sent.
We started to implement an experimental version of Pregel in ArangoDB. You need to check-out the pregel branch of ArangoDB in order to play with the following examples. Please be advised that the implementation is still in an early phase and very like to change. In this post we will provide a brief introduction to ArangoDB’s Pregel module by guiding you through the implementation of an example algorithm.
With ArangoDB 2.2 the new graph API was released featuring multi collection graphs (see blog). With the new version (2.2.1) of arangodb-java-driver the new graph API is supported. In the following you can find a small example of creating a graph with Java.
For the import via maven and configuring the driver, please read the Basics and Driver Setup. For the following we assume, that arangodbDriver is a configured instance of the driver.
So let’s start the whole thing…
This version is deprecated. Download the new version of ArangoDB
With the 2.2 release we proudly announce that we now offer the feature of multi collection graphs. This allows you to group an arbitrary set of ArangoDB collections into one graph. In order to do this grouping you execute the following steps in arangosh or Foxx: 1. Require the general-graph module and create a graph.
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var graph_module = require("org/arangodb/general-graph"); var graph = graph._create("myGraph"); |
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graph._addVertexCollection("person"); graph._addVertexCollection("publication"); graph._addVertexCollection("university"); graph._addVertexCollection("company"); |
FOSDEM is an absolutely open and free conference in Brussels, Belgium. The conference offers an impressive amount of developer rooms discussing a broad range of technical topics, including NoSQL and graphs.
After a funny and productive ArangoDB hackathon weekend Frank and I arrived at FOSDEM on Sunday noon. We were looking forward to the talks in the graph devroom, but unfortunately for us it was not possible to enter the room (it was overfull, indicating a great quality of talks).
At the next speakers change Frank and I managed to slip into the room and could enjoy two inspiring talks by Neo4J.
Afterwards it was my turn to present the graph visualization interface in ArangoDB in a still crowded room (slides).
After my presentation, we handed out all our ArangoDB t-shirts to our fans.
Michael handing out T-Shirts to the audience
All together it was a great experience and a really huge amount of people visiting the same conference which impressed me a lot.
Thanks for the team at the Graph Processing devroom for giving me the opportunity to speak and for organizing such a great devroom.
We will meet again next year.
so long,
Michael
you now have the opportunity to visualize your data graphically, using the “Graphs” tab in the admin interface.
In this post i will explain you how to do this:
Step 1) Configure the Interface
At first you have to configure the interface to display exactly the data you desire.
For the dataset you have two options:
Then the interface offers you several advanced options:
Configuration of GraphViewer