QUEL query languages

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Family Query language
Designed by Michael Stonebraker
First appeared 1976; 40 years ago (1976)
Major implementations
Influenced by

QUEL is a relational database query language, based on tuple relational calculus, with some similarities to SQL. It was created as a part of the Ingres DBMS effort at University of California, Berkeley, based on Codd's earlier suggested but not implemented Data Sub-Language ALPHA. QUEL was used for a short time in most products based on the freely available Ingres source code, most notably in an implementation called POSTQUEL supported by POSTGRES.[1] As Oracle and DB2 gained market share in the early 1980s, most companies then supporting QUEL moved to SQL instead.[citation needed] QUEL continues to be available as a part of the Ingres DBMS, although no QUEL-specific language enhancements have been added for many years.[when?]


QUEL statements are always defined by tuple variables, which can be used to limit queries or return result sets. Consider this example, taken from one of the first original Ingres papers:[2]

Example 1.1. Compute salary divided by age-18 for employee Jones.

 range of E is EMPLOYEE
 retrieve into W
 (COMP = E.Salary / (E.Age - 18))
 where E.Name = "Jones"

Here E is a tuple variable which ranges over the EMPLOYEE relation, and all tuples in that relation are found which satisfy the qualification E.Name = “Jones.” The result of the query is a new relation W, which has a single domain COMP that has been calculated for each qualifying tuple.

An equivalent SQL statement is:

 select (e.salary / (e.age - 18)) as comp
 from employee as e
 where e.name = "Jones"

QUEL is generally more "normalized" than SQL.[citation needed] Whereas every major SQL command has a format that is at least somewhat different from the others, in QUEL a single syntax is used for all commands.[citation needed]

For instance, here is a sample of a simple session that creates a table, inserts a row into it, and then retrieves and modifies the data inside it and finally deletes the row that was added (assuming that name is a unique field).

create student(name = c10, age = i4, sex = c1, state = c2)
range of s is student
append to s (name = "philip", age = 17, sex = "m", state = "FL")
retrieve (s.all) where s.state = "FL"
replace s (age=s.age+1)
retrieve (s.all)
delete s where s.name="philip"

Here is a similar set of SQL statements:

 create table student(name char(10), age int, sex char(1), state char(2))
 insert into student (name, age, sex, state) values ("philip", 17, "m", "FL")
 select * from student where state = "FL"
 update student set age=age+1
 select * from student
 delete from student where name="philip"

Note that syntax varies significantly between commands, and that even similar commands like insert and update use different styles.

Another feature of QUEL was a built-in system for moving records en-masse into and out of the system. Consider this command:

copy student(name=c0, comma=d1, age=c0, comma=d1, sex=c0, comma=d1, address=c0, nl=d1)
into "/student.txt"

which creates a comma-delimited file of all the records in the student table. The d1 indicates a delimiter, as opposed to a data type. Changing the into to a from reverses the process. Similar commands are available in many SQL systems, but usually as external tools, as opposed to being internal to the SQL language. This makes them unavailable to stored procedures.

QUEL has an extremely powerful aggregation capability. Aggregates can be nested, and different aggregates can have independent by-lists and/or restriction clauses. For example:

 retrieve (a=count(y.i by y.d where y.str = "ii*" or y.str = "foo"),b=max(count(y.i by y.d)))

This example illustrates one of the arguably less desirable quirks of QUEL, namely that all string comparisons are potentially pattern matches. y.str = "ii*" matches all y.str values starting with ii.

See also[edit]


  1. ^ Stonebraker, M; Rowe, LA (May 1986). The design of POSTGRES (PDF). Proc. 1986 ACM SIGMOD Conference on Management of Data. Washington, DC. 
  2. ^ Stonebraker, Michael; Wong, Eugene; Kreps, Peter; Held, Gerald (1976). "The Design and Implementation of INGRES". ACM Transactions on Database Systems. 1 (3): 191. doi:10.1145/320473.320476. Retrieved 2016-09-14. 

Further reading[edit]