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.
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.
Note: We changed the name of the database in May 2012. AvocadoDB is now called ArangoDB. UNQL started with quite some hype last year. However, after some burst of activity the project came to a hold. So it seems, that – at least as a project – UNQL has been a failure. IMHO one of the major issues with the current UNQL is, that it tries to cover everything in NoSQL, from key-value stores to document-stores to graph-database. Basically you end up with greatest common divisor – namely key-value access. But with graph structures and also document-structures you really want to supports joins, paths or some sort of sub-structures. Apart from all the technical and theoretical benefits of SQL and what advantages the underlying theory has to offer, the major plus from an users point of view is that it is readable. You simple can see an SQL statement – be it in C, Java, Ruby – and understand what is going on. It is declarative, not imperative. With other imperative solution, like a fluent interface or a map-reduce, you need to understand the underlying syntax or language. With SQL you only need to understand English – at least most of the time. And here I think is where UNQL is totally right. We need something similar for the NoSQL world. But it should not try to be a “fits all situation”. It should be a fit for 80% of the problems. For simple key-values stores a fluent-interface is indeed enough. For very complex graph traversals a traversal program must be written. For very complex map-reduces you might need to write a program – but check out Google’s talk (www.nosql-matters.org/program) about NoNoSQL. There they describe why they are developing a SQL-like interface for Map/Reduce. In my experience most of the time you have a set of collections holding different “types” of documents with some relations between them. One of the biggest advantages of document stores or graph databases is that you can have lists and sub-objects. The problem with SQL is, that it has no good way to deal with these structures. So I believe UNQL would be quite successful if it would concentrate on these strong advantages of NoSQL, instead of trying to unify everything – especially after hear Jan’s talk about a document query language at the NoSQL Cologne UG (an English version is also available). Cheers Frankaaa