relational dbms

Object-relational database



Another, related, aim is to bridge the gap between relational databases and the object-oriented modeling techniques used in programming languages such as Java, C++ or C#. However, a more popular alternative for achieving such a bridge is to use a standard relational database systems with some form of ORM software.

Whereas traditional RDBMS or SQL-DBMS products focused on the efficient management of data drawn from a limited set of data-types (defined by the relevant language standards), an object-relational DBMS allows software-developers to integrate their own types and the methods that apply to them into the DBMS. ORDBMS technology aims to allow developers to raise the level of abstraction at which they view the problem domain. This goal is not universally shared; proponents of relational databases often argue that object-oriented specification lowers the abstraction level.

An object-relational database can be said to provide a middle ground between relational databases and object-oriented databases (OODBMS). In object-relational databases, the approach is essentially that of relational databases: the data resides in the database and is manipulated collectively with queries in a query language; at the other extreme are OODBMSes in which the database is essentially a persistent object store for software written in an object-oriented programming language, with a programming API for storing and retrieving objects, and little or no specific support for querying.

Many SQL ORDBMSs on the market today are extensible with user-defined types (UDT) and custom-written functions (e.g. stored procedures). Some (e.g. SQL Server) allow such functions to be written in object-oriented programming languages, but this by itself doesn't make them object-oriented databases; in an object-oriented database, object orientation is a feature of the data model.

Comparison to RDBMS

An RDBMS might commonly involve SQL statements such as these:

  CREATE TABLE Customers  (
      Id          CHAR(12)    NOT NULL PRIMARY KEY,
      Surname     VARCHAR(32) NOT NULL,
      FirstName   VARCHAR(32) NOT NULL,
      DOB         DATE        NOT NULL
   SELECT InitCap(Surname) || ', ' || InitCap(FirstName)
     FROM Customers
    WHERE Month(DOB) = Month(getdate())
      AND Day(DOB) = Day(getdate())
Most current SQL databases allow the crafting of custom functions, which would allow the query to appear as:
   SELECT Formal(Id)
     FROM Customers
    WHERE Birthday(Id) = Today()

In an object-relational database, one might see something like this, with user-defined data-types and expressions such as BirthDay():

   CREATE TABLE Customers (
     Id           Cust_Id     NOT NULL  PRIMARY KEY,
     Name         PersonName  NOT NULL,
     DOB          DATE        NOT NULL
   SELECT Formal(C.Id )
     FROM Customers C
    WHERE BirthDay (C.DOB ) = TODAY;
The object-relational model can offer another advantage in that the database can make use of the relationships between data to easily collect related records. In an address book application, an additional table would be added to the ones above to hold zero or more addresses for each user. Using a traditional RDBMS, collecting information for both the user and their address requires a "join":
    SELECT InitCap(C.Surname) || ', ' || InitCap(C.FirstName),
      FROM Customers C join Addresses A ON A.Cust_Id=C.Id -- the join
     WHERE"New York"
The same query in an object-relational database appears more simply:
   SELECT Formal(C.Name )
     FROM Customers C
    WHERE"New York" -- the linkage is 'understood' by the ORDB


Object-relational database management systems grew out of research that occurred in the early 1990s. That research extended existing relational database concepts by adding object concepts. The researchers aimed to retain a declarative query-language based on predicate calculus as a central component of the architecture. Probably the most notable research project, Postgres (UC Berkeley), spawned two products tracing their lineage to that research: Illustra and PostgreSQL.

In the mid-1990s, early commercial products appeared. These included Illustra (Illustra Information Systems, acquired by Informix Software which was in turn acquired by IBM), Omniscience (Omniscience Corporation, acquired by Oracle Corporation and became the original Oracle Lite), and UniSQL (UniSQL, Inc., acquired by KCOMS). Ukrainian developer Ruslan Zasukhin, founder of Paradigma Software, Inc., developed and shipped the first version of Valentina database in the mid-1990s as a C++ SDK. By the next decade, PostgreSQL had become a commercially viable database and is the basis for several products today which maintain its ORDBMS features.

Computer scientists came to refer to these products as "object-relational database management systems" or ORDBMSs.

Many of the ideas of early object-relational database efforts have largely become incorporated into SQL:1999. In fact, any product that adheres to the object-oriented aspects of SQL:1999 could be described as an object-relational database management product. For example, IBM's DB2, Oracle database, and Microsoft SQL Server, make claims to support this technology and do so with varying degrees of success.

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