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N1QL versus SQL

The most important difference between N1QL and SQL is the data model. Other notable differences relate to the projection, selection, and filtering of data.

Data Model

In a relational database, data is constrained to tables with uniform structure. The following example consists of two tables, Employee and Employers, with Name as the primary key.

EMPLOYEE
Name | SSN | Wage
-----------------------------------------------------------------------
Jamie | 234 | 123
Steve | 123 | 456

SCHEMA:
Name -> String of width 100
SSN -> Number of width 9
Wage -> Number of width 10

EMPLOYERS:
-----------------------------------------------------------------------
 Name_Key  | Company   | Start | End
 Jamie     | Yahoo     | 2005  | 2006
 Jamie     | Oracle    | 2006  | 2012
 Jamie     | Couchbase | 2012  | NULL

By contrast, N1QL handles data as free-form documents, gathered into large collections called keyspaces. There is no uniformity; nor is there any logical proximity shared by objects of the same data shape within the keyspace. The relational data from the above example might therefore appear as follows:

 (HRData keyspace)
 {
     'Name': 'Jamie'
     'SSN': 234
     'Wage': 123
     'History':
      [
       ['Yahoo', 2005, 2006],
       ['Oracle', 2006, 2012],
     ]
 },

 {
     'Name': Steve
     'SSN':  123,
     'Wage': 456,
 }

Data Projection

In a relational database, when an SQL query is run, a set of rows is returned; each row consisting of one or more columns, and the columns being the same for each row. A header can be retrieved, to obtain metadata about each column.

Query:
SELECT Name, Company
    FROM Employee, Employers
    WHERE Name_Key = Name
Result:
	Name | Company
	----------------
	Jamie | Oracle
	Jamie | Yahoo
	Jamie | Couchbase
	----------------

By contrast, N1QL permits data reshaping, by embedding statement-attributes in the desired result-object shape. Like SQL, N1QL allows fields to be renamed; using the AS keyword.

Query:
 SELECT Name, History, {'FullTime': true} AS 'Status'
      FROM HRData
Result:
	{
	'Name': 'Jamie',
	'History':
		[
		['Yahoo', 2005, 2006],
		['Oracle', 2006, 2012],
		['Couchbase', 2012, null]
		],
	'Status': { 'FullTime': true }
	}
	{
	'Name': 'Steve',
	'Status': { 'FullTime': true }
	}

Data Selection

In N1QL, the FROM clause is used to select between data sources (keyspaces). If HRData is a keyspace, the following statement selects the Name attribute from all documents in the HRData keyspace that have a Name attribute defined.

SELECT Name FROM HRData

Each document can also regard itself as a data source, and run a query over its nested elements. Such nested elements are addressed using the dot (.) operator to descend a level, and the square-bracket ( [ ] ) operator to index into an array element.

  SELECT FullTime FROM HRData.Status
{
     'FullTime': true
}

The selected fields can also be renamed using the AS operator, as in SQL:

SELECT firstjob FROM HRData.History[0] AS firstjob
{
     'firstjob': ['Yahoo', 2005, 2006]
}

SELECT firstjob[2] FROM HRData.History[0] AS firstjob
{
     'firstjob[2]': 2006
}

Data Filtering

N1QL supports the WHERE clause, but with slight differences from SQL.

Similarly to SQL, the dot ( . ) and the square bracket ( [] ) operators can be used to access nested elements as they are used in SELECT clauses.

N1QL data can be irregularly shaped: hence, undefined values are recognized as distinct from null. N1QL provides a complementary set of operators like IS MISSING, in addition to standard operators like IS NULL. New conversions, for example from non-zero integer-values to Boolean value true, are also supported.

Most standard SQL functions (for example, LOWER()) are defined. In addition to the standard filtering-predicates, N1QL provides new operators to work with arrays in documents: ANY, SOME, and EVERY. ANY and SOME evaluate a condition for each element, and return true if any element meets the condition. EVERY also evaluates a condition for each element; except that it returns true only if all elements matched the condition.