I just came across a question about how to create highscore lists or leaderboards in ArangoDB, and how they would work when compared to Redis sorted sets.

This blog post tries to give an answer on the topic and also detailed instructions and queries for setting up highscore lists with ArangoDB. The additional section “Extensions” explains slightly more advanced highscore list use cases like multi-game highscore lists, joining data and maintaining a “last updated” date.

A highscore list in Redis

Highscore lists are normally used to quickly determine who’s currently at the top, so we obviously..

I often find myself searching for certain commits using git log and friends. While I really love the power and flexibility that come with the git and other Unix command-line tools, sometimes it can be more convenient to use a database to filter and aggregate commit data.

I gave it a quick try yesterday and imported the commit history of ArangoDB’s Git repository into ArangoDB and ran some queries on the data.

Contained in 2.5 are some small but useful AQL language improvements plus several AQL optimizer improvements.

We are working on further AQL improvements for 2.5, but work is still ongoing. This post summarizes the improvements that are already completed and will be shipped with the initial ArangoDB 2.5 release.

In the upcoming ArangoDB 2.5 (current devel branch) a new optimizer rule move-calculations-down was added. Jan showcases in his latest blog post how queries with calculations could benefit from this new optimiser rule.

The most powerful way to query your data in ArangoDB is by using ArangoDB’s own query language, AQL. In the past using AQL in your JavaScript code sadly would often require writing long, unwieldy strings. This made writing complex queries difficult and could often lead to subtle syntax errors or mistakes.

The ArangoDB Query Builder (AQB) is a JavaScript node packaged module that provides a fluid API for writing AQL queries in plain JavaScript. And if you’re using ArangoDB 2.3, the aqb module is already available to your Foxx applications. Let’s say we want to perform the following query in..

While on a retreat in Belgium, we found some spare time to work on improvements for AQL. These will be shipped with ArangoDB version 2.4, and are already available in the devel version for testing from now on.

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?”

Answer:

First we have to define an AQL-query:

String query = "for i in GRAPH_EDGES('Academical', null) return i";

In our..

The major new feature in ArangoDB 2.3 is the shiny new AQL query optimizer and executor. These parts of ArangoDB have been rewritten in 2.3 to make AQL much better for our end users.

MongoDB is a document DB whereas ArangoDB is a multi-model DB supporting documents, graphs and key/values within a single database. When it comes to data modeling and data querying, they pursue somewhat different approaches.

In a Nutshell: In MongoDB, data modeling is “aggregate-oriented”, avoiding relations and joins. On the other side, everybody has probably used relational databases which organize the data in tables with relations and try to avoid as much redundancy as possible. Both approaches have their pros and cons. ArangoDB is somewhat in-between: You can both model and query your..

This version is deprecated. Download the new version of ArangoDB

We are proud to present ArangoDB 2.3. The first beta version is now available for download from our web-site or you can use “brew install –unstable arangodb” under Mac OS X. You can also look into the nightly documentation for more information.

Please note that the main feature of this release contains a complete rewrite of the query engine, allowing much more optimizations than before – especially in the cluster case. It would be very helpful for us, if you could test this query engine as much as possible. If you find any..