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AQL Improvements for 2.4

02Query LanguageTags:

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.

Here’s a short overview of the improvements:

Collect with count

A common use case in query languages is to count the number of documents returned by a query. The AQL solution for this has been to use the LENGTH function and a subquery:

This is quite long and probably unintuitive for people which have used SQL for years.

We therefore now allow using the following alternative version:

Read more on Jan’s Blog

A Tour Around the New AQL Query Optimizer

00Query LanguageTags:

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.

Since one of the initial releases, ArangoDB has been shipped with AQL, the ArangoDB Query Language. AQL has since then been ArangoDB’s most versatile way of executing simple and also the not-so-simple queries.

I’ll start with an overview of query execution in previous versions of ArangoDB, and then explain the new engine and explain the differences.

Read more on Jan’s Blog

Modeling Data in MongoDB vs ArangoDB

05Architecture, Documentation, Graphs, Query LanguageTags: ,

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 data in a “relational way” but also in an “aggregate-oriented way”, depending on your use case. ArangoDB offers joins, nesting of sub-documents and multi-collection graphs. More info

Modifying AQL

02GeneralTags:

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.

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.

More info

AQL: Querying a nosql database the elegant & comfortable way

07Query LanguageTags:

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 collections, aggregate results, do some geo location stuff and even iterate over graphs.

So if you like the comfort of SQL but also the freedom of a schema free database, AQL is for you.

If you are interested in learning more about the concepts of ArangoDB checkout Jan’s talk and slides.

But let’s stop beating around the bush and rather have a look at specific examples.

More info

RFC – The ArangoDB/AvocadoDB query language

02Query LanguageTags: ,
Note: We changed the name of the database in May 2012. AvocadoDB is now called ArangoDB.

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.
More info

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