I have been looking at many AQL queries during the last few weeks…

Looking back, I can say that the JSON query execution plans provided by the explain() method have provided me with a lot of useful information about how the AQL optimizer had transformed a given query. This has helped testing and improving the query optimizer a great deal.

However, the JSON output produced by explain() is so detailed that even for the simplest cases queries it will span multiple screens. This is far too much for quickly assessing what a query will be doing and how it will be executed.

I therefore quickly put..

ArangoDB provides many options for finding and modifying data. Though there are several more specialized operation, data-modification AQL queries are the most general solution in ArangoDB. They allow to find documents using arbitrary filter criteria, and to modify or remove the documents once found.

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.

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..

ArangoDB comes with a powerful query language, called AQL. It combines all the different aspects in any easy-to-use query language. You can use joins as in SQL or graph queries as in Cypher. However, up to now it only supported read-queries.

FOR u IN users 
  FOR c IN cities 
    FILTER u.zip == c.zip 
    RETURN { 'name': u.name, 'city': c.name }

Allows you to join the name of city a persons lives in. If you want to follow the social graph and mix in the neighbors, simply add a graph query.

FOR u IN users FOR c IN cities FILTER u.zip == c.zip RETURN { 'name': u.name, 'city': c.name, 'knows':..

Note: The following article was originally written as an answer in ArangoDB google group. It may help other people to understand the scope of ArangoDB and/or AQL, so we posted it here as well.

AQL, the query language, provides access to the data which is stored inside collections. The collections contain documents, identified by unique keys.

Having a long history with relational databases and having worked for a lot of years with SQL some people find it a bit inconvenient querying nosql databases e.g. via REST. Others have rather complex data models and need nevertheless an elegant and convenient way for querying. And we all love clean and simple interfaces.

ArangoDB comes with a couple of options for querying the data, among offer it implements the “ArangoDB Query Language” (AQL).

AQL is a declarative query language for simple and also very complex queries. Unless like in other nosql databases you can also query across..

The REST API for AvocadoDB is already available and stable and people are writing APIs using it. Awesome. As AvocacoDB offers more complex data structures like graphs and lists REST is not enough. We implemented a first version of a query language some time ago which is very similar to SQL and UNQL.