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Entries in N1QL (1)

Monday
Oct122015

Exploring CouchBase N1QL

Couchbase recently announced Non-first Normal Form Query Language (N1QL) – pronounced “Nickel” – a virtually complete SQL language implementation for use with document databases, and implemented within the Couchbase server 4.0.

I recently took a quick look. 

Most of the examples use the sample films documents shown below (this is the same sample data we created for MongoDB in this post):

2015-10-05_16-43-02 n1ql

N1QL allows us to perform basic queries to retrieve selected documents or attributes of selected documents:

 

N1QL allows us to access nested documents within the JSON structure using array notation. So for instance in the example below Actors[0] refers to the first nested document within the actors array:

 

We can query for subdocuments which match a search criteria using WHERE ANY syntax:

 

The UNNEST command allows embedded documents to be “joined” back to the parent document. So here we get one result for each Actor who starred in film 200, with the film title included in the results:

 

 

 

The UNNEST command allows us to perform the equivalent of joins between parent and children documents where the child documents are nested within the parent. N1QL also allows us to join across disparate documents, providing that one of the document collections contains a reference to the primary key in the other.

So for instance if we had a bucket of documents that contains the primary keys of “overdue” films in our imaginary (and by now definitely struggling) DVD store, then we can join that to the films collection to return just those films:

 

N1QL also contains DML statements allowing us to manipulate the contents of documents, and DDL statements allowing creation and modification of indexes.

N1QL is ambitious attempt to bring SQL into the world of document databases. It’s interesting to consider that as the same time that companies like CouchBase are introducing SQL support into their database, that companies like Oracle are introducing strong JSON support into their SQL-based database. It would seem that the two worlds are coming together.